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āļāļąāļāļĐāļ°:
Appsflyer, Google Ads, Google Analytics
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Bášąng cáŧ nhÃĒn hoáš·c kinh nghiáŧm tháŧąc tášŋ tÆ°ÆĄng ÄÆ°ÆĄng.
- 5 nÄm kinh nghiáŧm trong mášĢng kinh doanh quášĢng cÃĄo, tiášŋp tháŧ, tư vášĨn hoáš·c truyáŧn thÃīng (và dáŧĨ: tÃŽm kiášŋm, mᚥng xÃĢ háŧi, thiášŋt báŧ di Äáŧng, quášĢng cÃĄo hiáŧn tháŧ và video).
- 5 nÄm kinh nghiáŧm biÊn soᚥn và trÃŽnh bà y cÃĄc náŧi dung hưáŧng Äášŋn khÃĄch hà ng (và dáŧĨ: bà i thuyášŋt trÃŽnh chà o hà ng, cÃĒu chuyáŧn hoáš·c tà i liáŧu tÃģm tášŊt) cho cÃĄc nhÃģm kinh doanh.
- 5 nÄm kinh nghiáŧm trong mášĢng ThÃīng tin chuyÊn sÃĒu váŧ ngưáŧi tiÊu dÃđng và tháŧ trưáŧng, Äo lưáŧng truyáŧn thÃīng và báŧi cášĢnh bášĢo mášt.
- 5 nÄm kinh nghiáŧm khai thÃĄc cÃĄc náŧn tášĢng Äo lưáŧng, sáŧ liáŧu phÃĒn tÃch và lášp mÃī hÃŽnh phÃĒn bổ.
- Kinh nghiáŧm triáŧn khai/Äiáŧu cháŧnh Chiášŋn lưáŧĢc Äo lưáŧng, phÃĒn tÃch web hoáš·c chiášŋn lưáŧĢc phÃĒn báŧ theo lưáŧĢt nhášĨp khÃīng phášĢi láš§n cuáŧi cÃđng, Äo lưáŧng trÊn nhiáŧu thiášŋt báŧ, theo dÃĩi lưáŧĢt chuyáŧn Äáŧi, tháŧ nghiáŧm theo Äáŧa lÃ―, máŧĐc tÄng/máŧĐc gia tÄng, Äo lưáŧng táŧŦ tráŧąc tuyášŋn Äášŋn ngoᚥi tuyášŋn, nhášp dáŧŊ liáŧu ngoᚥi tuyášŋn.
- Kinh nghiáŧm váŧ cÃĄc háŧ tháŧng Äo lưáŧng, phÃĒn tÃch trang web, quášĢn lÃ― quan háŧ khÃĄch hà ng (CRM) và háŧ tháŧng dáŧŊ liáŧu hà ng Äáš§u cáŧ§a bÊn tháŧĐ ba.
- Kinh nghiáŧm váŧ cÃĄc náŧn tášĢng phÃĒn báŧ áŧĐng dáŧĨng như Appsflyer, theo dÃĩi trÊn Meta/Tiktok bášąng cÃĄc náŧn tášĢng lášŊng nghe cáŧng Äáŧng mᚥng xÃĢ háŧi (và dáŧĨ: Sprinklr, Traackr hoáš·c CreatorIQ).
- Kinh nghiáŧm là m viáŧc và cáŧng tÃĄc váŧi nháŧŊng ngưáŧi cÃģ quyáŧn quyášŋt Äáŧnh tᚥi cÃīng ty dáŧch váŧĨ quášĢng cÃĄo/cÃīng ty khÃĄch hà ng mua quášĢng cÃĄo.
- Kiášŋn tháŧĐc váŧ háŧ sinh thÃĄi quášĢng cÃĄo káŧđ thuášt sáŧ và nháŧŊng thay Äáŧi váŧ quyáŧn riÊng tư.
- Kiášŋn tháŧĐc váŧ cÃĄc cháŧĐc nÄng Äo lưáŧng cáŧ§a Google trÊn cÃĄc náŧn tášĢng quášĢng cÃĄo và truyáŧn thÃīng, bao gáŧm cášĢ Google Ads, Search Ads 360 và Google Analytics.
- Doanh nghiáŧp thuáŧc máŧi loᚥi hÃŽnh và quy mÃī tin tưáŧng và o cÃĄc giášĢi phÃĄp quášĢng cÃĄo vưáŧĢt tráŧi cáŧ§a Google Äáŧ phÃĄt triáŧn trong mÃīi trưáŧng tiášŋp tháŧ khÃīng ngáŧŦng biášŋn Äáŧng ngà y nay. Bᚥn mang trong mÃŽnh niáŧm Äam mÊ bÃĄn hà ng, sáŧą hiáŧu biášŋt váŧ truyáŧn thÃīng tráŧąc tuyášŋn và lÃēng quyášŋt tÃĒm giÚp khÃĄch hà ng Äᚥt ÄÆ°áŧĢc sáŧą thà nh cÃīng láŧn nhášĨt. Bᚥn hà nh Äáŧng váŧi tinh tháš§n là m cháŧ§, nhanh nhᚥy thÃch áŧĐng váŧi máŧi thay Äáŧi, tÃŽm kiášŋm nháŧŊng cÃĄch tháŧĐc máŧi mang tÃnh chiášŋn lưáŧĢc Äáŧ liÊn táŧĨc Äem Äášŋn kášŋt quášĢ ášĨn tưáŧĢng và ngà y máŧt táŧt hÆĄn cho cášĢ Google lášŦn khÃĄch hà ng. Bᚥn xÃĒy dáŧąng máŧi quan háŧ ÄÃĄng tin cášy váŧi khÃĄch hà ng, tÃŽm hiáŧu nhu cáš§u kinh doanh cáŧ§a háŧ và dáŧąa và o ÄÃģ Äáŧ xÃĒy dáŧąng cÃĄc giášĢi phÃĄp hiáŧu quášĢ giÚp khÃĄch hà ng Äᚥt ÄÆ°áŧĢc nháŧŊng máŧĨc tiÊu láŧn lao nhášĨt. Bᚥn gáš·t hÃĄi thà nh cÃīng cÃđng Äáŧi ngÅĐ bÃĄn hà ng, Äáŧnh hÃŽnh tÆ°ÆĄng lai cáŧ§a ngà nh quášĢng cÃĄo trong káŧ· nguyÊn AI và tᚥo dášĨu ášĨn tháŧąc sáŧą Äáŧi váŧi hà ng triáŧu cÃīng ty cÅĐng như hà ng táŧ· ngưáŧi dÃđng Äáš·t tráŧn niáŧm tin và o Google cho nháŧŊng máŧĨc tiÊu quan tráŧng nhášĨt.
- Trong vai trÃē nà y, bᚥn sáš― giÚp cÃĄc nhà quášĢng cÃĄo máŧ ráŧng phᚥm vi sáŧ dáŧĨng cÃĄc giášĢi phÃĄp Äo lưáŧng và phÃĒn báŧ cáŧ§a Google Äáŧ thÚc ÄášĐy máŧĐc Äáŧ trưáŧng thà nh cáŧ§a hoᚥt Äáŧng Äo lưáŧng. Bᚥn sáŧ háŧŊu kiášŋn tháŧĐc chuyÊn mÃīn váŧ sášĢn phášĐm thuáŧc cÃĄc giášĢi phÃĄp Äo lưáŧng cáŧĨ tháŧ cáŧ§a Google vÃ ÄÆ°a ra giášĢi phÃĄp dáŧąa trÊn thÃīng tin chuyÊn sÃĒu thu thášp ÄÆ°áŧĢc. Bᚥn sáš― là m viáŧc váŧi Kháŧi KhÃĄch hà ng chiášŋn lưáŧĢc (LCS) và giÚp cÃĄc nhà quášĢng cÃĄo triáŧn khai nháŧŊng cÃīng ngháŧ Äo lưáŧng máŧi nhášĨt Äáŧ thÚc ÄášĐy máŧĐc Äáŧ trưáŧng thà nh cáŧ§a hoᚥt Äáŧng Äo lưáŧng tᚥi khu váŧąc ÄÃīng Nam à (SEA). Bᚥn sáš― vášn dáŧĨng kiášŋn tháŧĐc váŧ cÃĄc phÆ°ÆĄng phÃĄp trong ngà nh, xu hưáŧng truyáŧn thÃīng káŧđ thuášt sáŧ, khášĢ nÄng giášĢi quyášŋt vášĨn Äáŧ và káŧđ nÄng cáŧng tÃĄc Äáŧ thuyášŋt pháŧĨc nhà quášĢng cÃĄo tháŧąc hiáŧn cÃĄc biáŧn phÃĄp cáš§n thiášŋt, nhášąm thÚc ÄášĐy LáŧĢi táŧĐc Äáš§u tư (ROI) cho hoᚥt Äáŧng truyáŧn thÃīng bášąng cÃĄch tÃch háŧĢp dáŧŊ liáŧu vÃ ÄÆ°a ra quyášŋt Äáŧnh váŧ máš·t phÃĒn bổ. Bᚥn sáš― là m viáŧc theo sáŧą Äiáŧu pháŧi cáŧ§a lÃĢnh Äᚥo cášĨp quáŧc gia và cÃģ tháŧ sáš― phÃĄt triáŧn cÃĄc kášŋ hoᚥch Äo lưáŧng cho tášp háŧĢp cÃĄc khÃĄch hà ng, phÃĄt triáŧn cÃĄc kášŋ hoᚥch kÃch hoᚥt và theo dÃĩi tiášŋn Äáŧ tháŧąc hiáŧn cÃĄc kášŋ hoᚥch Äó.
- CÃĄc nhÃģm thuáŧc kháŧi KhÃĄch hà ng chiášŋn lưáŧĢc (LCS) cáŧ§a Google là cÃĄc Äáŧi tÃĄc chiášŋn lưáŧĢc và cáŧ vášĨn Äáš§u ngà nh, Äáŧng hà nh cÃđng cÃĄc thÆ°ÆĄng hiáŧu và cÃīng ty quášĢng cÃĄo hà ng Äáš§u thášŋ giáŧi. ChÚng tÃīi khÃīng ngáŧŦng khuyášŋn khÃch khÃĄch hà ng tư duy váŧ hoᚥt Äáŧng kinh doanh cáŧ§a háŧ, Äáŧng tháŧi thÚc ÄášĐy cÃĄch Google cÃģ tháŧ háŧ tráŧĢ háŧ tÄng trưáŧng. ChÚng tÃīi tášp trung và o viáŧc giÚp cÃĄc khÃĄch hà ng nà y thÃch áŧĐng váŧi nháŧŊng thay Äáŧi láŧn trong ngà nh và thÚc ÄášĐy hiáŧu suášĨt kinh doanh vưáŧĢt tráŧi bášąng cÃĄch cung cášĨp tráŧn báŧ giášĢi phÃĄp quášĢng cÃĄo cáŧ§a Google áŧ máŧĐc giÃĄ cᚥnh tranh trÊn Google TÃŽm kiášŋm, YouTube, Äo lưáŧng, và nhiáŧu náŧn tášĢng khÃĄc. Là máŧt thà nh viÊn cáŧ§a kháŧi LCS, bᚥn sáš― cÃģ cÆĄ háŧi Äáš·c biáŧt Äáŧ kinh doanh nháŧŊng cÃīng ngháŧ tiÊn tiášŋn nhášĨt, là m viáŧc váŧi cÃĄc quášĢn lÃ― cášĨp cao, tÃĄc Äáŧng Äášŋn cÃĄc chiášŋn lưáŧĢc Äáŧnh hÃŽnh tháŧ trưáŧng và tᚥo ra kášŋt quášĢ tháŧąc tášŋ, cÃģ ášĢnh hưáŧng ÄÃĄng káŧ Äášŋn cÃĄc doanh nghiáŧp láŧn trÊn toà n cáš§u, cÅĐng như thÚc ÄášĐy sáŧą tÄng trưáŧng cáŧ§a Google.
- Khai thÃĄc hoᚥt Äáŧng sáŧ dáŧĨng sášĢn phášĐm và tÃnh nÄng trong Analytics, Äáŧng tháŧi háŧ tráŧĢ cÃĄc chuyÊn gia sášĢn phášĐm khÃĄc trong cÃĄc trưáŧng háŧĢp phÃĒn bổ.
- Trao Äáŧi váŧi khÃĄch hà ng váŧ tÃnh nÄng Äo lưáŧng nÃĒng cao hoáš·c Äo lưáŧng toà n pháŧ u.
- Pháŧi háŧĢp váŧi cÃĄc nhÃģm thÃĒm nhášp tháŧ trưáŧng Äáŧ Äiáŧu cháŧnh sášĢn phášĐm cho phÃđ háŧĢp váŧi cÃĄc chÆ°ÆĄng trÃŽnh tà i tráŧĢ và thu hÚt khÃĄch hà ng.
- Triáŧn khai chiášŋn lưáŧĢc cho khu váŧąc ÄÃīng Nam à (SEA) bášąng cÃĄch tư vášĨn cho khÃĄch hà ng và ra mášŊt sášĢn phášĐm, tÄng máŧĐc Äáŧ sáŧ dáŧĨng cÃĄc sášĢn phášĐm náŧn tášĢng quyáŧn riÊng tư và máŧĐc Äáŧ tÃch háŧĢp dáŧŊ liáŧu cáŧ§a bÊn tháŧĐ nhášĨt.
- Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
āļāļąāļāļĐāļ°:
Compliance, Budgeting, ERP
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Secure Strategic Funding & Financial Instruments: Source and negotiate short-term and long-term funding solutions such as working capital loans, project finance, bonds, and equity to support operational and investment needs; manage relationships with financial institutions both onshore and offshore to achieve optimal terms and minimize financing costs..
- Develop and Maintain Financial Models & Analysis: Build, adjust, and update consolidated and project-specific financial models to support strategic decisions, financial ...
- Loan & Covenant Management: Oversee loan agreements and ensure full compliance with financial covenants; manage loan drawdowns, repayments, interest obligations, and dividend policies while coordinating with relevant parties to maintain lender confidence..
- Financial Planning, Budgeting & Reporting: Support the development and control of annual budgets, cash flow forecasts, and investment plans; prepare financial reports and presentations for management, Board of Directors, shareholders, and auditors to ensure transparency and fiscal discipline..
- Operational Finance, Risk & Compliance: Handle daily financial operations including invoice issuance, payment processing, ERP data entry (e.g., SAP), and document management; monitor financial risks such as FX and interest rates, ensure compliance with internal controls and external regulations, and coordinate with audit and regulatory bodies..
- Bachelor's or Master's degree in finance, Accounting, Business Administration or related fields.
- 5-7 years experience in banking or corporate finance function in any companies.
- Good financial planning and financial model knowledge.
- Experience in managerial accounting and budgeting management is required.
- Creativity, problem solving skills, negotiation and systematic thinking.
- Fluent in English both written and verbal (Minimum 750 TOEIC score).
- Goal-Oriented, Unity, Learning, Flexible.
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļāļąāļāļāļģāļāļīāļāļāļĢāļĢāļĄāļŠāđāļāđāļŠāļĢāļīāļĄāļāļēāļĢāļāļēāļĒ āđāļāļ·āđāļāļāļĢāļ°āļāļļāđāļ/āļāļĨāļąāļāļāļąāļāļŠāļīāļāļāđāļēāļāļēāļāļĢāđāļēāļāļāđāļēāļŠāļđāđāļāļđāđāļāļĢāļīāđāļ āļ āļāļēāļĄāđāļāđāļēāļŦāļĄāļēāļĒāļāļēāļĢāļāļēāļĒāđāļĨāļ°āļāļĨāļĒāļļāļāļāđāļāļāļāļāļĢāļīāļĐāļąāļāļŊāđāļāđāļāđāļĨāļ°āļāļĨāļļāđāļĄāļŠāļīāļāļāđāļē āļāļąāđāļāđāļāļāļĨāļļāđāļĄāļŠāļīāļāļāđāļē Alcohol āđāļĨāļ° āļāļĨāļļāđāļĄāļŠāļīāļāļāđāļē Non-Alcohol āđāļāļāđāļāļāļāļēāļ TT.
- āļāļąāļāļāļģ āđāļĨāļ°āļāļģāđāļŠāļāļāđāļāļāļāļēāļĢāļāļģāđāļāļīāļāļāļēāļāļĢāļēāļĒāļāļąāļāļŦāļ§āļąāļāđāļāļ·āđāļāļāļĨāļąāļāļāļąāļāļŠāļīāļāļāđāļēāļŠāļđāđāļāļđāđāļāļĢāļīāđāļ āļ āđāļāļāđāļāļāļāļēāļ TT āđāļŦāđāđāļŦāļĄāļēāļ°āļŠāļĄāđāļĨāļ°āļŠāļāļāļāļĨāđāļāļāļāļąāļāļŠāļāļēāļāļāļēāļĢāļāđāļāļēāļĢāđāļāđāļāļāļąāļāđāļāļāļ·āđāļāļāļĩāđ / āļāđāļāļāļāļēāļāļāļēāļĢāļāļēāļĒ.
- āļāļīāļāļāļēāļĄāļāļĨāļāļēāļĢāļāļģāđāļāļīāļāļāļēāļāļāļēāļāļāļēāļĢāļāļģāļāļīāļāļāļĢāļĢāļĄāļāļēāļĄāđāļāļāļĢāļēāļĒāļāļąāļāļŦāļ§āļąāļ āđāļāļĢāļēāļĒāļāļĨāļīāļāļ āļąāļāļāđ āļĢāļēāļĒāļĢāđāļēāļāļāđāļē āđāļĨāļ° āļāļēāļāļŦāļ§āļąāļāđāļŦāđāļĢāđāļēāļāļāđāļēāđāļāđāļāļĨāļąāļāļāļąāļāļŠāļīāļāļāđāļēāļŠāļđāđāļāļđāđāļāļĢāļīāđāļ āļāđāļāđāļĄāļēāļāļāļķāđāļ āļāļēāļĄāđāļāđāļēāļŦāļĄāļēāļĒāļāļĩāđāļ§āļēāļāđāļ§āđ āļāļĢāđāļāļĄāļāļąāđāļ ...
- āļāļąāļāļāļģāđāļĨāļ°āļāļģāđāļŠāļāļāđāļāļāļāļēāļāļāļēāļĢāļŠāļĢāđāļēāļāļ āļēāļāļĨāļąāļāļĐāļāđāļŦāļāđāļēāļĢāđāļēāļ āđāļāļāđāļāļāļāļēāļ TT āđāļŦāđāļŠāļāļāļāļĨāđāļāļāļāļąāļ Brand Direction.
- āļāļīāļāļāļēāļĄ āđāļĨāļ° āđāļāđāļāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļāļīāļāļāļĢāļĢāļĄāļāļāļāļāļđāđāđāļāđāļ āđāļāļ·āđāļāļāļģāļĄāļēāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļŠāļāļēāļāļāļēāļĢāļāđ āļāļēāļĢāđāļāđāļāļāļąāļāđāļāļāļąāļāļāļļāļāļąāļ.
- āļāļāļāļāļĢāļ§āļāļāļĨāļēāļāđāļāļ·āđāļāļŠāļāļąāļāļŠāļāļļāļāļāļēāļĢāļāļģāđāļāļīāļāļāļēāļāļāļāļāļāļĩāļĄāļāļēāļĒāđāļāđāļāđāļĨāļ°āļāđāļāļāļāļēāļāļāļēāļĒāđāļāļĩāđāļĒāļ§āļāļąāļāļāļīāļāļāļĢāļĢāļĄāļāļēāļāļāđāļēāļāđāļāļĢāļāļĄāļēāļĢāđāđāļāđāļāļāļīāđāļāđāļŦāđāđāļāđāļāđāļāļāļēāļĄāđāļāļāļāļēāļĢāļāļģāđāļāļīāļāļāļēāļ āđāļĨāļ°āļŠāļāļāļāļĨāđāļāļāļāļąāļāļāļĨāļĒāļļāļāļāđāļāļāļāļāļĢāļīāļĐāļąāļāļŊ.
- āļāļēāļāļāļ·āđāļāđāļāļĩāđāđāļāđāļĢāļąāļāļĄāļāļāļŦāļĄāļēāļĒ.
- āļāļāļāļĢāļīāļāļāļēāļāļĢāļĩāđāļāļŠāļēāļāļēāļāļēāļĢāļāļĨāļēāļ āļāļĢāļīāļŦāļēāļĢāļāļļāļĢāļāļīāļ āļŦāļĢāļ·āļāļŠāļēāļāļēāļāļ·āđāļāđāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāđāļāļāļģāđāļŦāļāđāļāļāļēāļ 2 āļāļĩ āļāļķāđāļāđāļ āđāļāļāđāļēāļ Trade Marketing.
- āļĄāļĩāļāļąāļāļĐāļ°āļāļēāļĢāđāļāđ Microsoft Office āđāļāļĒāđāļāļāļēāļ° āđāļāļĢāđāļāļĢāļĄ Excel āđāļĨāļ° Power Point āđāļāđāđāļāđāļāļāļĒāđāļēāļāļāļĩ.
- āļŠāļēāļĄāļēāļĢāļāļāļąāļāļĢāļāļĒāļāļāđāđāļĨāļ°āļĄāļĩāđāļāļāļąāļāļāļĩāđāļĢāļāļĒāļāļāđ /āļāļāļīāļāļąāļāļīāļāļēāļāļāđāļēāļāļāļąāļāļŦāļ§āļąāļāđāļāđ.
āļāļąāļāļĐāļ°:
DevOps, Kafka, Kubernetes
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Define solution blueprints, roadmaps, and system architectures aligned with banking strategies, TOGAF standards, and enterprise architecture principles.
- Ensure solutions adhere to regulatory requirements (BOT, PDPA, AML/KYC, Basel III, IFRS9).
- Business Alignment & Requirement Analysis.
- Collaborate with business units (Retail, SME, Corporate, Wealth, Trade Finance) to analyze requirements and translate them into scalable technical solutions.
- Perform gap analysis between as-is and to-be architectures, ensuring alignment with digital transformation initiatives.
- Technical Leadership & Governance.
- Provide technical leadership for solution delivery teams, including developers, DevOps, and security engineers.
- Act as the key interface with Portfolio Architects to ensure architectural compliance.
- Drive adherence to enterprise standards for authentication, authorization, DevSecOps pipelines, monitoring, and high availability.
- Integration & Data Architecture.
- Design secure integration patterns using APIs, ESB, Kafka/event streaming, and micro services.
- Ensure seamless data flow across channels (mobile banking, internet banking, branch, contact center).
- Govern data lineage, data masking, and DWH/analytics integration for reporting and regulatory submissions.
- Security & Compliance.
- Embed security-by-design principles in all solutions.
- Ensure compliance with internal security standards, PDPA, cybersecurity frameworks, and central bank regulations.
- Collaborate with IT Risk and Cybersecurity teams to address vulnerabilities and audit requirements.
- High Availability & Resilience.
- Define HA/DR solutions based on application criticality ratings (RTO/RPO).
- Work with Infrastructure and Cloud teams to design active-active and disaster recovery setups.
- Validate solutions against performance, scalability, and recovery testing benchmarks.
- Innovation & Emerging Tech.
- Evaluate cloud-native architectures, container platforms (Kubernetes, OpenShift), and fintech APIs for strategic advantage.
- Recommend the adoption of AI/ML, RPA, and blockchain technologies where applicable.
- Education & Experience.
- Bachelor s or higher degree in Computer Science, Computer Engineering, or related field.
- 7-10 years of experience in application/system design, with at least 5 years in financial services.
- Proven track record in banking solution delivery across channels (mobile, branch, digital lending, payments, trade finance).
- Experience in core banking integration, digital channels, and regulatory reporting.
- Strong expertise in cloud transformation (hybrid/on-prem + Azure/AWS/GCP).
- Technical Skills.
- Architecture & Integration: Microservices, SOA, API-first design, Event-driven architecture, ESB, Kafka.
- DevSecOps & CI/CD: Jenkins, GitLab, Docker, Kubernetes, Terraform, Ansible.
- Database & Data Platforms: Oracle Exadata, SQL Server, PostgreSQL; Data Lakehouse (Databricks, Snowflake).
- Security & Compliance: IAM, OAuth2/JWT, PKI, LDAP/EntraID, encryption, data masking.
- Performance & Resilience: Load balancing, caching, Redis HA, database sharding, monitoring tools (Dynatrace, SolarWinds).
- Business & Soft Skills.
- Strong analytical and problem-solving ability.
- Ability to bridge business strategy with technical execution.
- Excellent communication with executives, regulators, and technical teams.
- Experienced in Agile/Scaled Agile delivery, working with cross-functional squads.
- Comfort in high-pressure environments with multiple stakeholders.
- Preferred Certifications (Optional but Advantageous).
- Architecture & Cloud: TOGAF, AWS/Azure/GCP Certified Architect.
- Agile Delivery: Certified Scrum Master, SAFe Architect.
- Data & Integration: Kafka, Kubernetes, or Databricks Certification.
- Contact: (K.Kanyarut).
- You have read and reviewed Krung Thai Bank Public Company Limited's Privacy Policy at https://krungthai.com/th/content/privacy-policy. The Bank does not intend or require the processing of any sensitive personal data, including information related to religion and/or blood type, which may appear on copy of your identification card. Therefore, please refrain from uploading any documents, including copy(ies) of your identification card, or providing sensitive personal data or any other information that is unrelated or unnecessary for the purpose of applying for a position on the website. Additionally, please ensure that you have removed any sensitive personal data (if any) from your resume and other documents before uploading them to the website.
- The Bank is required to collect your criminal record information to assess employment eligibility, verify qualifications, or evaluate suitability for certain positions. Your consent to the collection, use, or disclosure of your criminal record information is necessary for entering into an agreement and being considered for the aforementioned purposes. If you do not consent to the collection, use, or disclosure of your criminal record information, or if you later withdraw such consent, the Bank may be unable to proceed with the stated purposes, potentially resulting in the loss of your employment opportunity with.
āļāļąāļāļĐāļ°:
Project Management, Excel, Power point
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Execute new project with IT development team and end users related to user account management.
- Maintain the consolidated staff & outsource information (Provisioning System) according to staff logistic process with HR and outsource logistic process with all business functions.
- Operate user account for Krungsri applications and Auto applications and 3rd party applications according to user request and user access matrix (UAM).
- Disable and/or delete user account for Krungsri & Auto applications and 3rd party applications upon user resignation.
- Submit request to 3rd parties such as BOT, ITMX, and external bank to operate user account according to user request.
- Prepare test case and execute user acceptance test related to user account management in various project.
- Coordinate with IT Application & Infra owner for onetime data in order to update user account into system in case onetime data by project.
- Summarize monthly reports and submit to IT Account management team lead respectively.
- Perform review all application user profile & user access matrix according to plan.
- Support prepare data for auditor program.
- Apply now if you have these advantages.
- More than 5-10 years experience in IT, IT security or IT Audit with good attitude is acceptable.
- Experience in UAM of banking application and all application.
- Experience in project management.
- Experience in support & trouble shooting of user account management.
- Advance in MS office such as Microsoft Word, Excel, Excel-Macro, Power Point.
- Ability to multitask work requirements aligned with team lead and related party.
- Why join Krungsri?.
- As a part of MUFG (Mitsubishi UFJ Financial Group), we a truly a global bank with networks all over the world.
- We offer a striking work-life balance culture with hybrid work policies (2 days in office per week minimum).
- Unbelievable benefits such as attractive bonuses, employee loan with special rates and many more..
- Apply now before this role is close. **.
- FB: Krungsri Career(http://bit.ly/FacebookKrungsriCareer [link removed]).
- LINE: Krungsri Career (http://bit.ly/LineKrungsriCareer [link removed]).
- Talent Acquisition Department
- Bank of Ayudhya Public Company Limited
- 1222 Rama III Rd., Bangpongpang, Yannawa, Bangkok 10120.
- āļŦāļĄāļēāļĒāđāļŦāļāļļ āļāļāļēāļāļēāļĢāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāđāļĨāļ°āļāļ°āļĄāļĩāļāļąāđāļāļāļāļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāļđāđāļŠāļĄāļąāļāļĢ āļāđāļāļāļāļĩāđāļāļđāđāļŠāļĄāļąāļāļĢāļāļ°āđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāđāļāđāļēāļĢāđāļ§āļĄāļāļēāļāļāļąāļāļāļāļēāļāļēāļĢāļāļĢāļļāļāļĻāļĢāļĩāļŊ.
- Remark: The bank needs to and will have a process for verifying personal information related to the criminal history of applicants before they are considered for employment with the bank..
- Applicants can read the Personal Data Protection Announcement of the Bank's Human Resources Function by typing the link from the image that stated below.
- EN (https://krungsri.com/b/privacynoticeen).
- āļāļđāđāļŠāļĄāļąāļāļĢāļŠāļēāļĄāļēāļĢāļāļāđāļēāļāļāļĢāļ°āļāļēāļĻāļāļēāļĢāļāļļāđāļĄāļāļĢāļāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļŠāđāļ§āļāļāļēāļāļāļĢāļąāļāļĒāļēāļāļĢāļāļļāļāļāļĨāļāļāļāļāļāļēāļāļēāļĢāđāļāđāđāļāļĒāļāļēāļĢāļāļīāļĄāļāđāļĨāļīāļāļāđāļāļēāļāļĢāļđāļāļ āļēāļāļāļĩāđāļāļĢāļēāļāļāļāđāļēāļāļĨāđāļēāļ.
- āļ āļēāļĐāļēāđāļāļĒ (https://krungsri.com/b/privacynoticeth).
āļāļąāļāļĐāļ°:
Product Development, Problem Solving, Good Communication Skills, Japanese
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Conduct vehicle and bench testing for performance and reliability of EE / CCS system & diagnostics.
- Read test specifications, identify preparation requirements & draft testing plan for each vehicle milestone.
- Understand component/system logs to troubleshoot and coordinate with designer for countermeasure.
- Liaise with Technical teams (Regional- NMAP/Local, NML); for connected car service implementation.
- Support supplier technical reviews, facilitate change management and approval for connected car services.
- Liaise with govt for certification/regulation & coordinate for logistics of test parts.
- Report, project progress & development progress.
- Travel to Japan and other ASEAN countries for vehicle testing, technical feasibility study and discussions.
- Support benchmarking, re-creation of field issues & overall product development towards providing connectivity for vehicles.
- Qualifications Bachelor's degree or higher.
- Good problem solving and problem analysis skill.
- Good communication skills in English (TOEIC 550+) and/ or Japanese language (N4 or above) are a plus.
- Computer literate with knowledge in software or mobile application (Preferred).
- Automotive OEM work experience with Infrastructure background is a plus.
- project management and collaboration experience.
- If you are interested in this job role, please prepare your updated resume or LinkedIn profile for the application process through the Nissan Job Portal.
- Only shortlisted candidate will be contacted for an interview".
- For more information about Nissan's products, services, and commitment to sustainable mobility, visit nissan-global.com. You can also follow us on Facebook, Instagram, Twitter and LinkedIn and see all our latest videos on YouTube.
- Why Nissan?.
- You will definitely get the right answers why you should join us through watching the video on YouTube.
- Bangkok Thailand
āļāļąāļāļĐāļ°:
Compliance, Risk Management
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Develop & Implement Data Governance Framework - Establish policies, standards, and best practices for data management.
- Ensure Data Quality & Integrity - Monitor and improve data accuracy, consistency, and completeness.
- Regulatory Compliance & Risk Management - Ensure adherence to data privacy laws (e.g., PDPA, GDPR) and mitigate risks.
- Define Data Ownership & Stewardship - Assign roles and responsibilities for data management across the organization.
- Manage Data Lineage & Metadata - Maintain a data catalog, track data sources, and ensure proper documentation.
- Gather & Translate Business Requirements - Convert business needs into technical specifications for development teams.
- Document functional and non-functional requirements for data and technology projects.
- System & Process Improvement - Identify gaps in existing systems and workflows and recommend improvements.
- Stakeholder Communication - Act as a bridge between business users and IT teams, simplifying complex technical concepts.
- Compliance & Security Considerations - Ensure data solutions align with governance policies and regulatory requirements.
- Bachelor s or Master s degree in Data Science, Information Management, Computer Science, Business Administration, or a related field.
- Certifications in Data Governance (e.g., DAMA CDMP), Data Privacy (e.g., CIPP/E, CIPM), or Risk Management are a plus.
- Experience in data governance, data management, or related fields.
- Skills in a leadership or managerial role, overseeing data governance initiatives.
- Proven track record in developing and implementing data governance frameworks, policies, and standards.
- Hands-on experience in data quality management, metadata management, and data lineage tracking.
- Strong background in regulatory compliance (e.g., PDPA, GDPR, CCPA) and risk management.
āļāļąāļāļĐāļ°:
Financial Analysis, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļ§āļļāļāļīāļāļēāļĢāļĻāļķāļāļĐāļēāļĢāļ°āļāļąāļāļāļĢāļīāļāļāļēāļāļĢāļĩāļāļķāđāļāđāļ āļāđāļēāļāļāļēāļĢāļāļąāļāļāļĩ āļāļĢāļīāļŦāļēāļĢāļāļļāļĢāļāļīāļ āļāļēāļĢāđāļāļīāļ āđāļĻāļĢāļĐāļāļĻāļēāļŠāļāļĢāđ āļāļēāļĢāļāļĨāļēāļ āļŦāļĢāļ·āļāļŠāļēāļāļēāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāđāļēāļāļāļēāļĢāļ§āļēāļāđāļāļāļĒāļļāļāļāļĻāļēāļŠāļāļĢāđ āđāļāļāļāļļāļĢāļāļīāļ āđāļāļāļāļēāļĢāđāļāļīāļ āļŦāļĢāļ·āļāļāļāļāļĢāļ°āļĄāļēāļ āļŦāļĢāļ·āļāļāļēāļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ.
- āļĄāļĩāļāļ§āļēāļĄāļĢāļāļāļĢāļđāđāđāļāļāļļāļĢāļāļīāļāļāļāļēāļāļēāļĢ āļāļĨāļīāļāļ āļąāļāļāđāđāļĨāļ°āļāļĢāļīāļāļēāļĢ āļĢāļ§āļĄāļāļķāļāļĄāļĩāļāļ§āļēāļĄāļĢāļđāđāļāđāļēāļāļāļēāļĢāļāļĨāļēāļ.
- āļĄāļĩāļāļ§āļēāļĄāļĢāļđāđāđāļĨāļ°āđāļāđāļēāđāļāļĢāļ°āļāļāļāļąāļāļāļĩ āđāļĨāļ°āļāļāļāļēāļĢāđāļāļīāļāļāļāļāļāļāļēāļāļēāļĢ.
- āļĄāļĩāļāļąāļāļĐāļ°āļāđāļēāļāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļĨāļ°āļāļĢāļ°āļĄāļ§āļĨāļāļĨāļāđāļāļĄāļđāļĨ āđāļĨāļ°āļāļēāļĢāļāļģāđāļŠāļāļ.
- āļŠāļēāļĄāļēāļĢāļāļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢ āļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļĨāļ°āđāļāđāļāļąāļāļŦāļēāđāļāļāļēāļ°āļŦāļāđāļēāđāļāđāļāļĩ.
- āļĄāļĩāļĄāļāļļāļĐāļĒāđāļŠāļąāļĄāļāļąāļāļāđāļāļĩāđāļāļĩ āļĄāļĩāļāļąāļāļĐāļ° āđāļĨāļ°āļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļāđāļāļāļēāļĢāļŠāļ·āđāļāļŠāļēāļĢāđāļāđāļāļĒāđāļēāļāļĄāļĩāļāļĢāļ°āļŠāļīāļāļāļīāļāļĨ.
- āļŠāļēāļĄāļēāļĢāļāđāļāđāļ āļēāļĐāļēāļāļąāļāļāļĪāļĐāļāļĒāļđāđāđāļāļĢāļ°āļāļąāļāļāļāđāļāđ-āļāļĩ.
- āļāđāļēāļāđāļāđāļāđāļēāļāđāļĨāļ°āļĻāļķāļāļĐāļēāļāđāļĒāļāļēāļĒāļāļ§āļēāļĄāđāļāđāļāļŠāđāļ§āļāļāļąāļ§āļāļāļāļāļāļēāļāļēāļĢāļāļĢāļļāļāđāļāļĒ āļāļģāļāļąāļ (āļĄāļŦāļēāļāļ) āļāļĩāđ https://krungthai.com/th/content/privacy-policy āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāđāļĄāđāļĄāļĩāđāļāļāļāļēāļŦāļĢāļ·āļāļāļ§āļēāļĄāļāļģāđāļāđāļāđāļāđ āļāļĩāđāļāļ°āļāļĢāļ°āļĄāļ§āļĨāļāļĨāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ āļĢāļ§āļĄāļāļķāļāļāđāļāļĄāļđāļĨāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļĻāļēāļŠāļāļēāđāļĨāļ°/āļŦāļĢāļ·āļāļŦāļĄāļđāđāđāļĨāļŦāļīāļ āļāļķāđāļāļāļēāļāļāļĢāļēāļāļāļāļĒāļđāđāđāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļāļāļāļāļāđāļēāļāđāļāđāļāļĒāđāļēāļāđāļ āļāļąāļāļāļąāđāļ āļāļĢāļļāļāļēāļāļĒāđāļēāļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāđāļāđ āļĢāļ§āļĄāļāļķāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļ āļŦāļĢāļ·āļāļāļĢāļāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§āļŦāļĢāļ·āļāļāđāļāļĄāļđāļĨāļāļ·āđāļāđāļ āļāļķāđāļāđāļĄāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļŦāļĢāļ·āļāđāļĄāđāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļŠāļĄāļąāļāļĢāļāļēāļāđāļ§āđāļāļāđāļ§āđāļāđāļāļāđ āļāļāļāļāļēāļāļāļĩāđ āļāļĢāļļāļāļēāļāļģāđāļāļīāļāļāļēāļĢāđāļŦāđāđāļāđāđāļāļ§āđāļēāđāļāđāļāļģāđāļāļīāļāļāļēāļĢāļĨāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ (āļāđāļēāļĄāļĩ) āļāļāļāļāļēāļāđāļĢāļāļđāđāļĄāđāđāļĨāļ°āđāļāļāļŠāļēāļĢāļāļ·āđāļāđāļāļāđāļāļāļāļĩāđāļāļ°āļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāļāļąāļāļāļĨāđāļēāļ§āđāļ§āđāļāļāđāļ§āđāļāđāļāļāđāđāļĨāđāļ§āļāđāļ§āļĒ āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļāđāļāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāļāļļāļāļāļĨāđāļāđāļēāļāļģāļāļēāļ āļŦāļĢāļ·āļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāļļāļāļŠāļĄāļāļąāļāļī āļĨāļąāļāļĐāļāļ°āļāđāļāļāļŦāđāļēāļĄ āļŦāļĢāļ·āļāļāļīāļāļēāļĢāļāļēāļāļ§āļēāļĄāđāļŦāļĄāļēāļ°āļŠāļĄāļāļāļāļāļļāļāļāļĨāļāļĩāđāļāļ°āđāļŦāđāļāļģāļĢāļāļāļģāđāļŦāļāđāļ āļāļķāđāļāļāļēāļĢāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ·āđāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāđāļāđāļēāļāļģāļŠāļąāļāļāļēāđāļĨāļ°āļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļāļēāļĄāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļ āđāļāļāļĢāļāļĩāļāļĩāđāļāđāļēāļāđāļĄāđāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļāļēāļĢāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄ āļŦāļĢāļ·āļāļĄāļĩāļāļēāļĢāļāļāļāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ āļēāļĒāļŦāļĨāļąāļ āļāļāļēāļāļēāļĢāļāļēāļāđāļĄāđāļŠāļēāļĄāļēāļĢāļāļāļģāđāļāļīāļāļāļēāļĢāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļāđāļāđ āđāļĨāļ°āļāļēāļ āļāļģāđāļŦāđāļāđāļēāļāļŠāļđāļāđāļŠāļĩāļĒāđāļāļāļēāļŠāđāļāļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāđāļāđāļēāļāļģāļāļēāļāļāļąāļāļāļāļēāļāļēāļĢ.
āļāļąāļāļĐāļ°:
Software Development, Research, Legal
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Develop, implement, and maintain cybersecurity policies, standards, and baselines that align with international best practices and regulatory requirements.
- Ensure continuous compliance with relevant laws, regulations, and industry frameworks (e.g., ISO/IEC 27001, NIST, GDPR).
- Strategic Advisory.
- Provide expert cybersecurity consulting to internal departments, project teams, and external partners to ensure the protection of information assets and systems.
- Act as a trusted advisor in security architecture, secure software development, and infrastructure protection.
- Risk Management.
- Conduct cyber risk assessments and threat modeling across systems and processes.
- Recommend and implement mitigation strategies to address identified vulnerabilities and risks.
- Support incident response planning and execution, including post-incident analysis and reporting.
- Compliance Monitoring & Improvement.
- Monitor internal and external compliance with cybersecurity policies and standards.
- Analyze security weaknesses and gaps, and propose enhancements to strengthen the organization s security posture.
- Research & Innovation.
- Stay current with emerging technologies, global cybersecurity standards, and threat intelligence.
- Lead research initiatives to evaluate new tools, frameworks, and methodologies for improving cybersecurity practices.
- Integrate findings into the continuous development of cybersecurity policies and controls.
- Collaboration & Reporting.
- Collaborate with IT, legal, compliance, and business units to align cybersecurity initiatives with organizational goals.
- Prepare reports and presentations for senior management on cybersecurity metrics, risks, and strategic initiatives..
- Desired qualifications.
- Bachelor Degree or higher in computer science, information technology, Cyber Security or related field.
- 3-5 years experience in Cyber Security, IT Infrastructure and Data Network.
- Knowledge: Cyber Security, Computer Data Network, Programing, IT & Cyber Security Operation.
- Training experience: Security Plus (Sec+) or equivalent certifications, compliance ISO-27001, CSA-STAR, PCI-DSS is advantage.
- CISSP or CISA/CIAM is advantage.
- Good attitude, Strong communication and presentation skills.
āļāļąāļāļĐāļ°:
Statistics, Big Data, SQL
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Data Science Foundations: Strong foundation in data science, statistics, and advanced data analytics, including data visualization to communicate insights effectively.
- Exploratory Data Analysis (EDA): Skilled in performing EDA to uncover patterns, detect anomalies, and generate meaningful insights from data.
- Experimentation & Testing: Skilled in designing A/B tests or other experimental designs to measure business impact, analyze results, and communicate findings clearly to stakeholders.
- Machine Learning & AI.
- Model Development & Deployment: Experience in building, deploying, and optimizing machine learning models on large datasets.
- Generative AI (GenAI): Opportunity to work on GenAI projects that drive innovation and impactful business solutions.
- Problem-Solving & Collaboration.
- Analytical & Problem-Solving Skills: Strong analytical and problem-solving abilities focused on deriving actionable insights from data.
- Team Collaboration: Ability to work effectively both independently and as part of a collaborative team, contributing to shared project goals.
- Technical Expertise.
- Proficiency in Big Data Technologies: Expertise in Spark, PySpark, and SQL for large-scale data processing focused on feature creation for machine learning models and data analysis tasks.
- Programming Skills: Strong proficiency in Python for data analysis and machine learning (including libraries like Pandas, PySpark, Scikit-learn, XGBoost, LightGBM, Matplotlib, Plotly, Seaborn, etc.).
- Python Notebooks: Familiarity with Jupyter, Google Colab, or Apache Zeppelin for interactive data analysis and model development.
- Platform Experience: Experience in using PySpark on cloud platforms such as Azure Databricks or other platforms (including on-premise) is a plus.
- Education & Experience.
- Educational Background: Bachelor s or advanced degree in Data Science, Statistics, Computer Science, Computer Engineering, Mathematics, Information Technology, Engineering, or related fields.
- Work Experience: At least 2-3 years of relevant experience in Data Science, Analytics, or Machine Learning, with demonstrated technical expertise and a proven track record of driving data-driven business solutions.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
āđāļĄāđāļāļģāđāļāđāļāļāđāļāļāļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļģāļāļēāļ
āļāļąāļāļĐāļ°:
Creativity, Thai, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļķāļāļāļēāļ
- Laleda Tailor is seeking a creative and motivated Social Media Marketing Intern to join our team. This internship offers an exciting opportunity to gain hands-on experience in fashion branding, content creation, and social media marketing within a premium tailor-made clothing business.
- Create and schedule engaging content for Instagram, Facebook, and TikTok
- Support photo/video shoots including behind-the-scenes, styling, and product features
- Monitor social media performance and suggest optimizations
- Stay updated on trends in men s fashion and tailor-made clothing
- Coordinate with the marketing team to brainstorm new campaign ideas
- Ensure all content aligns with brand image and tone.
- University student or recent graduate in marketing, communications, fashion, or related fields
- Interest in fashion, styling, and social media
- Basic skills in Canva, CapCut, or Adobe Creative Suite
- Strong communication and organizational skills
- Able to work independently and collaborate in a small team.
- Why Join Us?.
- At Laleda Tailor, you ll gain practical experience in fashion marketing and content strategy. This is a great opportunity to build your portfolio, understand real-world brand communication, and receive mentorship in a growing business environment..
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
2 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
AutoCAD
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŋ18,000 - āļŋ22,000, āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āđāļāļĩāļĒāļāđāļāļāļāļēāļāļāđāļēāļāđāļāļēāļĄāļāļĩāđāđāļāđāļĢāļąāļāļĄāļāļāļŦāļĄāļēāļĒ
- āļāļđāđāļĨāļāļąāļāđāļāđāļāđāļāļāļāļĩāđāđāļāļĩāļĒāļ āđāļĨāļ°āđāļāđāļĢāļąāļāļāļēāļāļ āļēāļĒāļāļāļāļāļĒāđāļēāļāđāļāđāļāļĢāļ°āļāļ
- āļāļđāđāļĨāļāļ§āļāļāļļāļĄ āđāļĨāļ°āļāļĢāļ§āļāđāļāđāļāđāļĄāļĨāļāđāđāļĨāļ°āļāļīāđāļāļāļēāļāļāđāļāđāļāļāđāļŦāđāļāļĢāļāļāļēāļĄāļāļĩāđāļāļāļāđāļāļāđāļ§āđ.
- āļ§āļļāļāļīāļāļēāļĢāļĻāļķāļāļĐāļē āļāļ§āļŠ. āļŦāļĢāļ·āļ āļāļĢāļīāļāļāļēāļāļĢāļĩ āļŠāļēāļāļēāđāļāļĩāļĒāļāđāļāļāđāļāļĢāļ·āđāļāļāļāļĨ, āđāļĒāļāļē āļŦāļĢāļ·āļāļŠāļēāļāļēāļāļ·āđāļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ.
- āļĄāļĩāļāļ§āļēāļĄāļĢāļąāļāļāļīāļāļāļāļāļŠāļđāļ āļāļĢāļāļāđāļāđāļ§āļĨāļē āđāļĨāļ°āļŠāļēāļĄāļēāļĢāļāļāļģāļāļēāļāļ āļēāļĒāđāļāđāđāļĢāļāļāļāļāļąāļāđāļāđ.
- āļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļāđāļāļāļēāļĢāđāļāđāđāļāļĢāđāļāļĢāļĄ SolidWorks āđāļĨāļ° AutoCAD āđāļāđāļāļĒāđāļēāļāļāļģāļāļēāļ.
- āļŠāļēāļĄāļēāļĢāļāļāđāļēāļāđāļĨāļ°āļāļĩāļāļ§āļēāļĄāđāļāļāļ§āļīāļĻāļ§āļāļĢāļĢāļĄāđāļāđāļāļđāļāļāđāļāļ āđāļāđāļ āđāļāļāđāļāļĢāļāļŠāļĢāđāļēāļ, āđāļāļāļāļīāļāļāļąāđāļ, āđāļāļāļāļĢāļ°āļāļāļ.
- āļŦāļēāļāļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāđāļāļāļēāļāđāļāļĩāļĒāļāđāļāļāđāļāđāļĢāļāļāļēāļāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄ āđāļāļĒāđāļāļāļēāļ°āļāļēāļāļāļąāļ āļŦāļĢāļ·āļ āļŠāļīāļāļāđāļēāđāļāđāļāļāļĢāđāļāļĨāļēāļŠāļāļ°āļāļīāļāļēāļĢāļāļēāđāļāđāļāļāļīāđāļĻāļĐ.
- āļĄāļĩāļāļ§āļēāļĄāļĢāļđāđāđāļāļĩāđāļĒāļ§āļāļąāļāļĄāļēāļāļĢāļāļēāļāļāļēāļĢāđāļāļĩāļĒāļāđāļāļ.
- āļŦāļēāļāļŠāļēāļĄāļēāļĢāļāļāļāļāđāļāļāļ§āļąāļŠāļāļļ (BOQ) āđāļāđ āļāļ°āđāļāđāļāļāļĢāļ°āđāļĒāļāļāđāļāļĒāđāļēāļāļĒāļīāđāļ.
- āļāļąāļāļĐāļ°āđāļāļāļēāļĢāļŠāļ·āđāļāļŠāļēāļĢ āđāļĨāļ°āļŠāļēāļĄāļēāļĢāļāļāļģāļāļēāļāļĢāđāļ§āļĄāļāļąāļāļ§āļīāļĻāļ§āļāļĢāļŦāļĢāļ·āļāļāđāļēāļĒāļāļĨāļīāļāđāļāđāļāļĩ.
- āđāļāđāļĢāļđāđ āļāļāļāđāļĢāļĩāļĒāļāļĢāļđāđāđāļāļāđāļāđāļĨāļĒāļĩāļŦāļĢāļ·āļāđāļāļĢāđāļāļĢāļĄāđāļŦāļĄāđāđ.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
3 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Thai, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŋ15,000 - āļŋ22,000, āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ, āļĄāļĩāļāđāļēāļāļāļĄāļĄāļīāļāļāļąāđāļ
- āļāļģāđāļŠāļāļāļāļēāļĒāļāļĨāļīāļāļ āļąāļāļāđāļāļāļāļāļĢāļīāļĐāļąāļāļāļąāļāļĨāļđāļāļāđāļēāļāļĨāļļāđāļĄāļāļđāđāļĢāļąāļāđāļŦāļĄāļē āđāļĢāļāļāļēāļāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄ āđāļāđāļēāļāļāļāđāļāļĢāļāļāļēāļĢ āļŠāļīāļāļāđāļē āđāļāđāļ āļāđāļāļĢāđāļāļĒāļŠāļēāļĒāđāļāļāđāļē āļĢāļēāļāļ§āļēāļāļŠāļēāļĒāđāļāļāđāļē āļāđāļāļāđāļģāļāļĩ/āļāđāļģāđāļŠāļĩāļĒ FRP Tank āđāļāđāļāļāđāļ.
- āļ§āļēāļāđāļāļāļāļēāļĢāļāļēāļĒ āļāļģāļĒāļāļāļāļēāļĒāđāļŦāđāđāļāđāļāļēāļĄāđāļāđāļēāļŦāļĄāļēāļĒāļāļĩāđāļāļģāļŦāļāļ.
- āļ§āļēāļāđāļāļāļāļēāļĢāļŦāļēāļĨāļđāļāļāđāļēāļĢāļēāļĒāđāļŦāļĄāđ āļāļģāļŦāļāļāđāļāļ§āļāļēāļāļāļēāļĢāļāļđāđāļĨāļĨāļđāļāļāđāļēāļĢāļēāļĒāđāļāđāļēāđāļāļ·āđāļāļĢāļąāļāļĐāļēāļāļēāļāļĨāļđāļāļāđāļē āļāļĢāđāļāļĄāļāļąāđāļāļŠāļĢāđāļēāļāļŠāļąāļĄāļāļąāļāļāļ āļēāļāļāļĩāđāļāļĩāļāļąāļāļĨāļđāļāļāđāļēāļāļĒāđāļēāļāļāđāļāđāļāļ·āđāļāļ.
- āļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāđāļāļĄāļđāļĨāļāļēāļĢāļāļēāļĒ āļŠāļĢāļļāļāļāļąāļāļŦāļē āļāļąāļāļāļģāļĢāļēāļĒāļāļēāļāđāļĨāļ°āļĢāđāļ§āļĄāļāļģāđāļŠāļāļāđāļāļ§āļāļēāļāļāļēāļĢāļāļąāļāļāļēāļāļĨāļĒāļļāļĄāļāđāļāđāļēāļāļāļēāļĢāļāļēāļĒ.
- āļĄāļĩāļāļ§āļēāļĄāļāļĢāļ°āļāļ·āļāļĢāļ·āļāļĢāđāļ āļĨāļ°āđāļāļĩāļĒāļāļĢāļāļāļāļāļāđāļāļāļēāļĢāļāļģāļāļēāļ āļāļāļāļāļēāļāļāđāļēāļāļēāļĒāļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļ āđāļĄāđāļāļāļāļŦāļĒāļļāļāļāļĒāļđāđāļāļąāļāļāļĩāđ.
- āļĄāļĩāļāļ§āļēāļĄāļāļāļāļ āļāļĒāļąāļāļāļģāļāļēāļ āļĢāļąāļāļāļēāļāļĩāļ āļāļąāļāļāļēāļĒ āļāļĢāđāļāļĄāļāļąāļāļāļēāļāļāđāļāļ.
- āļĄāļĩāļāļļāļāļĨāļīāļāļ āļēāļāļāļĩ āļĄāļāļļāļĐāļĒāļŠāļąāļĄāļāļąāļāļāđāļāļĩ āļŠāļēāļĄāļēāļĢāļāđāļāļĢāļāļēāļāđāļāļĢāļāļāđāļāđ.
- āļĄāļĩāļĢāļāļĒāļāļāđāļŠāļģāļŦāļĢāļąāļāđāļāđāđāļāļāļēāļĢāļāļģāļāļēāļ āđāļĨāļ°āļĄāļĩāđāļāļāļāļļāļāļēāļāļāļąāļāļāļĩāđāļĢāļāļĒāļāļāđāļŠāđāļ§āļāļāļļāļāļāļĨ.
āļāļąāļāļĐāļ°:
Product Owner, Legal, Negotiation
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Define the AI product vision, strategy, and roadmap in alignment with Siam Piwat s business goals.
- Identify high-value opportunities for AI adoption that create measurable business outcomes (e.g.,revenue growth, cost reduction, operational efficiency, enhanced customer experience).
- Manage and prioritize the AI product backlog, ensuring a balance between quick wins and long-term innovation.
- Serve as the key link between business stakeholders, executives, technical teams, and data science teams to ensure alignment and clarity of objectives.
- Define, monitor, and continuously improve KPIs for AI products, including accuracy, adoption rate, engagement, and business impact.
- Strong understanding of trends and innovation, being integrated into local and regional AI communities.
- Lead experimentation and prototyping to validate AI concepts before scaling to production.
- Ensure all AI initiatives comply with relevant legal, security, ethical, and data privacy standards (e.g., PDPA).
- Develop, mentor, and grow the capabilities of the AI product team, fostering a culture of innovation and data-driven decision-making.
- Build strong relationships with internal and external stakeholders to align AI initiatives with broader organizational strategy.
- Stakeholder satisfaction and cross-team alignment.
- Bachelor s degree in Computer Science, Data Science, Business Administration, or related field (Master s degree preferred).
- 7+ years of experience in product management or related roles, with at least 3 years in AI, machine learning, or data-driven products.
- Proven track record of delivering AI or ML solutions from concept to production.
- Being data driven and ability to analyze complex data.
- Experience working with cross-functional teams including data scientists, engineers, and business stakeholders.
- Familiarity with agile methodologies and product lifecycle management.
- Strong understanding of Generative AI/ML concepts, data pipelines, and model lifecycle.
- Ability to translate complex technical concepts into business-friendly language.
- Knowledge of data privacy regulations (e.g., PDPA, GDPR) and ethical AI practices.
- Strategic thinking with strong business acumen.
- Excellent communication, presentation, and negotiation skills.
- Problem-solving mindset with a focus on delivering business impact.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
1 āļāļĩāļāļķāđāļāđāļ
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŋ15,000 - āļŋ16,000, āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļ§āļēāļāđāļāļāļāļēāļĢāļāļāļŠāđāļāļŠāļīāļāļāđāļē āđāļŦāđāđāļāđāļāđāļāļāļēāļĄāļāļģāļŦāļāļāļ§āļąāļāļŠāđāļāļĄāļāļāļāļāļāļāļģāļŠāļąāđāļāļāļ·āđāļ (Order).
- āļāļĢāļ§āļāļŠāļāļāļāļģāļŠāļąāđāļāļāļ·āđāļ (Order) āđāļĨāļ°āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļąāļāļāđāļēāļĒāļāļēāļĒāđāļāļĩāđāļĒāļ§āļāļąāļāļĢāļēāļĒāļāļēāļĢāļāļĩāđāļāļ°āļāļąāļāļŠāđāļ.
- āļāļĢāļ§āļāļŠāļāļāļāļģāļŠāļąāđāļāļāļ·āđāļāļĨāđāļ§āļāļŦāļāđāļē 1 āļŠāļąāļāļāļēāļŦāđ āđāļāļ·āđāļāđāļāđāļāđāļŦāđāļāđāļēāļĒāļāļēāļĒāļāļĢāļēāļ āđāļĨāļ°āļāļĢāļ°āđāļĄāļīāļāļāļ§āļēāļĄāļāļĢāđāļāļĄāļāļāļāļĢāļāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāļāļāļŠāđāļ.
- āļāļāļīāļāļąāļāļīāļāļēāļāļāļ·āđāļ āđ āļāļēāļĄāļāļĩāđāđāļāđāļĢāļąāļāļĄāļāļāļŦāļĄāļēāļĒāļāļēāļāļāļđāđāļāļąāļāļāļąāļāļāļąāļāļāļē.
- āđāļĄāđāļāļģāļāļąāļāđāļāļĻ.
- āļāļēāļĒāļļ 24-36 āļāļĩ.
- āļŠāļģāđāļĢāđāļāļāļēāļĢāļĻāļķāļāļĐāļēāļĢāļ°āļāļąāļ āļāļ§āļŠ. āļāļķāđāļāđāļ.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāđāļāļŠāļēāļĒāļāļēāļāļāļĒāđāļēāļāļāđāļāļĒ 1 āļāļĩ.
- āļĄāļĩāļāļ§āļēāļĄāļāļĨāđāļēāļāļīāļ āļāļĨāđāļēāļāļąāļāļŠāļīāļāđāļ āđāļĨāļ°āļŠāļ·āđāļāļŠāļēāļĢāļāļĒāđāļēāļāļāļąāļāđāļāļ.
- āļŠāļēāļĄāļēāļĢāļāđāļāđāļāļąāļāļŦāļēāđāļāļāļēāļ°āļŦāļāđāļēāđāļāđ.
- āđāļāļīāļāļāļēāļāļĄāļēāļāļģāļāļēāļāđāļāļāđāļāđ.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
1 āļāļĩāļāļķāđāļāđāļ
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŋ15,000 - āļŋ18,000, āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļāļąāļāļāļģāđāļāļāļāļēāļĢāļāļĨāļīāļ/āļāļĢāļĢāļāļļ āđāļāļ·āđāļāđāļŦāđāļŠāļāļāļāļĨāđāļāļāļāļąāļāļāļ§āļēāļĄāļāđāļāļāļāļēāļĢāļŠāļīāļāļāđāļēāđāļĨāļ°āļāļēāļĄāļāļ§āļēāļĄāļāđāļāļāļāļēāļĢāļāļāļāļĨāļđāļāļāđāļē.
- āļāļąāļāļāļģāđāļāļāļāļēāļĢāļŠāļąāđāļāļŠāļēāļĢāđāļāļĄāļĩ āđāļāļ·āđāļāđāļŦāđāđāļāļĩāļĒāļāļāļāļāđāļāļāļ§āļēāļĄāļāđāļāļāļāļēāļĢ.
- āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļąāļāļŠāđāļ§āļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ āļāļąāđāļāđāļāļŠāđāļ§āļ āļāļģāļāļāđāļŦāđāļāļĨāļīāļ/āļāļĢāļĢāļāļļāļŠāļīāļāļāđāļē, āļāļēāļĢāļāļīāļāļāđāļāļāļĢāļ°āļŠāļēāļāļāļēāļāđāļāļĩāđāļĒāļ§āļāļąāļāļāļēāļĢāļĢāļąāļāđāļāđāļēāļŠāļēāļĢāđāļāļĄāļĩ āļĢāļ§āļĄāļāļąāđāļ āļāļēāļĢāļĢāļąāļ-āļāđāļēāļĒāļŠāļīāļāļāđāļē.
- āļāļąāļāļāļģāđāļāļāļŠāļēāļĢāļāļēāļĢāļāļģāļāļēāļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļāļēāļĄāļĢāļ°āļāļ ISO 9001:2015.
- āļāļēāļāļāļ·āđāļāđ āļāļĩāđāđāļāđāļĢāļąāļāļĄāļāļāļŦāļĄāļēāļĒ.
- āđāļāļĻāļāļēāļĒ āļāļēāļĒāļļ 23 - 35 āļāļĩ.
- āļ§āļļāļāļīāļāļēāļĢāļĻāļķāļāļĐāļē āļāļ§āļŠ.āļāļķāđāļāđāļ.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāđāļēāļāļ§āļēāļāđāļāļāļāļĒāđāļēāļāļāđāļāļĒ 1 āļāļĩ.
- āļĄāļĩāļāļ§āļēāļĄāļĢāļđāđāļāđāļēāļāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļĨāļ°āļāļģāļāļ§āļāļāļēāļāđāļāļĄāļĩ.
- āļŠāļēāļĄāļēāļĢāļāđāļāđ MS Office āđāļāđāļāļĒāđāļēāļāļāļĩ.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
āđāļĄāđāļāļģāđāļāđāļāļāđāļāļāļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļģāļāļēāļ
āļāļąāļāļĐāļ°:
E-learning, Mandarin, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļēāļĢāđāļāđāļāļĄāđ
āđāļāļīāļāđāļāļ·āļāļ:
āļŋ15,000 - āļŋ30,000, āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļŠāļāļāļ āļēāļĐāļēāļāļĩāļāđāļāļ·āđāļāļāļēāļĢāļŠāļ·āđāļāļŠāļēāļĢ āļāļąāđāļāđāļāđāļĢāļ°āļāļąāļāļāļ·āđāļāļāļēāļāļāļāļāļķāļāļĢāļ°āļāļąāļ A2.
- āļŠāļāļāļāļāļāđāļĨāļāđāđāļŦāđāļāļąāļāļāļđāđāđāļĢāļĩāļĒāļāļ§āļąāļĒāļāļģāļāļēāļ.
- āļ§āļēāļāđāļāļāđāļĨāļ°āļāļąāļāđāļāļ·āđāļāļŦāļēāļāļēāļĢāļŠāļāļāđāļŦāđāđāļŦāļĄāļēāļ°āļŠāļĄāļāļąāļāļāļđāđāđāļĢāļĩāļĒāļ.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļŠāļāļāļ āļēāļĐāļēāļāļĩāļ (āđāļāđāļŦāļ§āļąāļ) āļĄāļēāļāđāļāļ
- āļŠāļēāļĄāļēāļĢāļāļŠāļ·āđāļāļŠāļēāļĢāđāļāđ 3 āļ āļēāļĐāļē āđāļāļĒ, āļāļąāļāļāļĪāļĐ āđāļĨāļ° āļāļĩāļ
- āđāļĄāđāļāļģāļāļąāļāļāļēāļĒāļļāđāļĨāļ°āđāļāļĻ
- āļĢāļąāļāļāļēāļĢāļŠāļāļ āđāļāđāļĒāđāļ āđāļŠāđāđāļāļāļąāļāļāļēāļāļđāđāđāļĢāļĩāļĒāļ..
- āļāđāļēāļāļāļāđāļāļ āļāļķāđāļāļāļąāļāļāļĢāļ°āļŠāļāļāļēāļĢāļāđ (āļāļĢāļļāļāļēāļĢāļ°āļāļļāđāļāđāļāļŠāļĄāļąāļāļĢ)..
- āļŠāļāđāļāļŠāļĄāļąāļāļĢ
- āļŠāđāļāđāļĢāļāļđāđāļĄāđāļĄāļēāļāļĩāđ [email protected]
- āđāļāļĢ. 02-3544525 āļŦāļĢāļ·āļ 088-235-1419.
- āļĄāļēāļĢāđāļ§āļĄāđāļāđāļāļŠāđāļ§āļāļŦāļāļķāđāļāđāļāļāļēāļĢāļāļąāļāļāļēāļĻāļąāļāļĒāļ āļēāļāļāđāļēāļāļ āļēāļĐāļēāđāļŦāđāļāļąāļāļāļāđāļāļĒāļāļąāļāļāļ°āļāļ° .
- āļĢāļąāļāļŠāļĄāļąāļāļĢāļāļĢāļđāļ āļēāļĐāļēāļāļĩāļ #ChineseLecturer #ParttimeJob #āļāļēāļāļāļāļāđāļĨāļāđ #MedcoachRecruitment.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
āđāļĄāđāļāļģāđāļāđāļāļāđāļāļāļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļģāļāļēāļ
āļāļąāļāļĐāļ°:
English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļēāļĢāđāļāđāļāļĄāđ
āđāļāļīāļāđāļāļ·āļāļ:
āļŋ15,000
- āļāļĢāļ°āļŠāļēāļāļāļēāļāļĢāļ°āļŦāļ§āđāļēāļāļĨāļđāļāļāđāļēāđāļĨāļ°āļāļĩāļĄāļāļēāļāđāļĢāļ·āđāļāļāļāļēāļĢāļŠāļāļąāļāļŠāļāļļāļāļāđāļēāļāđāļāļāļāļīāļāđāļĨāļ°āļāļēāļĢāļāļēāļĒāđāļāļ·āđāļāļāļāđāļ.
- āļāļąāļāļŦāļĄāļēāļĒāđāļĨāļ°āļāļĢāļ°āļŠāļēāļāļāļēāļĢāļāļĢāļ°āļāļļāļĄāļĢāļ°āļŦāļ§āđāļēāļāļĨāļđāļāļāđāļēāđāļĨāļ°āļāļĩāļĄāđāļāļāļāļīāļāļ āļēāļĒāđāļ.
- āđāļŦāđāļāļēāļĢāļŠāļāļąāļāļŠāļāļļāļāđāļāļāļāļīāļāļĢāļ°āļāļąāļāđāļĢāļāđāļĨāļ°āļāļĢāļ°āļŠāļēāļāļāļēāļ.
- āļŠāđāļāļāđāļāļāļąāļāļŦāļēāđāļāļāļāļīāļāļāļĩāđāļāļąāļāļāđāļāļāđāļŦāđāļāļĩāļĄāļ āļēāļĒāđāļ.
- āļāļīāļāļāļēāļĄāļāļēāļāļŠāļāļąāļāļŠāļāļļāļ.
- āļāļĢāļ°āļŠāļēāļāļāļēāļāđāļāļĢāļāļāļēāļĢāļāļąāļāļĨāļđāļāļāđāļēāđāļĨāļ°āļāļĩāļĄāļ āļēāļĒāđāļ.
- āļāļąāļāļāļēāļĢāļāļąāļāļŦāļĄāļēāļĒāđāļāļŠāļāļēāļāļāļĩāđāđāļĨāļ°āļāļēāļĢāđāļĒāļ·āļāļāļāđāļēāļāđāļāļāļāļīāļ.
- āļĢāļąāļāļĐāļēāļāļēāļĢāļŠāļ·āđāļāļŠāļēāļĢāļāļĩāđāļŠāļĄāđāļģāđāļŠāļĄāļāļĢāļ°āļŦāļ§āđāļēāļāļĨāļđāļāļāđāļēāđāļāļŠāļāļēāļāļāļĩāđāđāļĨāļ°āļāļĩāļĄ.
- āļāļģāļāļ§āļĒāļāļ§āļēāļĄāļŠāļ°āļāļ§āļāļāļēāļĢāļāļĢāļ°āļāļļāļĄāļāļāļāđāļĨāļāđāđāļĨāļ°āļāļēāļĢāļŠāļāļāļāļēāļāļēāļāđāļāļāļāļīāļ.
- āļāļąāļāļāļēāļĢāđāļāļāļŠāļēāļĢāđāļĨāļ°āđāļāļāļŠāļēāļĢāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļāļąāļāļĨāļđāļāļāđāļē.
- āļāļāđāļŦāļĄāđāļŦāļĢāļ·āļāļāļāļāļēāļĢāļĻāļķāļāļĐāļēāđāļĄāļ·āđāļāđāļĢāđāļ§āđ āļāļĩāđ (āļāļĢāļīāļāļāļēāļāļĢāļĩāļāļļāļāļŠāļēāļāļē āđāļāļĒāđāļāļāļēāļ° IT, āļ§āļīāļĻāļ§āļāļĢāļĢāļĄ āļŦāļĢāļ·āļāļāļļāļĢāļāļīāļ).
- āļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļēāļĢāļāļģāļāļēāļ 0-2 āļāļĩ.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļķāļāļāļēāļāļāđāļēāļāļāļĢāļīāļāļēāļĢāļĨāļđāļāļāđāļēāļŦāļĢāļ·āļāļāļēāļĢāļŠāļāļąāļāļŠāļāļļāļāļāđāļēāļāđāļāļāļāļīāļ āļāļ°āļāļīāļāļēāļĢāļāļēāđāļāđāļāļāļīāđāļĻāļĐ.
- āļ āļēāļĐāļēāļāļąāļāļāļĪāļĐ: āļŠāļēāļĄāļēāļĢāļāļŠāļ·āđāļāļŠāļēāļĢāđāļāđ (āļāļđāļ āļāđāļēāļ āđāļāļĩāļĒāļ).
- āđāļāđāļāđāļāļāļēāļĢāđāļāđāđāļāļĢāļ·āđāļāļāļĄāļ·āļ AI āđāļāļ·āđāļāļāđāļ§āļĒāļāļēāļ (ChatGPT, Claude, DeepSeek, Gemini āđāļāđāļāļāđāļ).
- āļāļļāđāļāđāļāļĒāļāļąāļ Microsoft Office Suite āđāļĨāļ° Google Workspace.
- āļŠāļēāļĄāļēāļĢāļāđāļĢāļĩāļĒāļāļĢāļđāđāļāļāļāļāđāđāļ§āļĢāđāđāļĨāļ°āļĢāļ°āļāļāđāļāļāļāļīāļāđāļŦāļĄāđāđāļāđ.
- āļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļāđāļāļāļēāļĢāļāļąāļāļāļēāļĢāđāļĨāļ°āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļĩāđāļāļĩ.
- āļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļāđāļāļāļēāļĢāļāļāļāļŠāļāļāļāļāļĒāđāļēāļāļŠāļĄāđāļģāđāļŠāļĄāļ.
- āļāļāļāļāļēāļĢāļŠāļ·āđāļāļŠāļēāļĢāļāļĒāđāļēāļāļāļĢāļāđāļāļāļĢāļāļĄāļē.
- āļĢāļąāļāļāļēāļĢāđāļĢāļĩāļĒāļāļĢāļđāđāļŠāļīāđāļāđāļŦāļĄāđāđ.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
5 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Research, Thai, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
- A Master s degree in Climatology, Meteorology, Atmospheric Science, Environmental Science, or a related field with a minimum of five (5) years of relevant professional experience in climatology or related areas is required.
- A Ph.D. in a related field may be considered in lieu of some experience, provided the candidate demonstrates strong applied expertise relevant to the position.
- Strong understanding of climate variability and weather-related hazards, including extreme rainfall, droughts, heatwaves, tropical cyclones, and severe storms, particul ...
- Proficiency in climate modeling, data processing, and visualization using R, Python, MATLAB, GIS, or other relevant statistical and geospatial tools.
- Familiarity with global and regional forecasting systems and platforms (e.g., ECMWF, CFS, GFS, WRF, RegCM), and experience working with climate datasets such as ERA5, CMIP6, CHIRPS, and CRU.
- Advanced understanding of seasonal and sub-seasonal prediction systems and their application in risk-informed planning and decision-making.
- Knowledge of climate risk assessment, disaster risk reduction (DRR), early warning systems (EWS), and climate change adaptation (CCA) concepts and planning frameworks.
- Demonstrated ability to generate and translate climate information into impact-based forecasts and advisory products relevant to agriculture, water resources, health, and disaster risk management.
- Experience in statistical downscaling, bias correction, and real-time error correction methods, including application of machine learning techniques.
- Proficiency in geospatial analysis, remote sensing data applications, and integration of spatial datasets into climate assessments.
- Strong analytical, diagnostic, and systems-level problem-solving skills.
- Proven ability to interpret and communicate complex scientific findings to technical and non-technical audiences, including policy- and decision-makers.
- Excellent communication and technical writing skills, including the development of scientific reports, policy briefs, proposals, training materials, and donor reporting.
- Strong stakeholder engagement and representation skills, and demonstrated ability to work effectively in cross-disciplinary, multicultural, and multi-stakeholder environments.
- Capacity to manage multiple assignments under tight deadlines while maintaining attention to detail and quality.
- Experience.
- A minimum of five (5) years of professional experience in operational climate forecasting, climate modeling, and climate data analysis.
- Experience collaborating with national meteorological and hydrological services, regional climate centers, governmental agencies, and/or international organizations.
- Demonstrated experience in developing climate products and integrating climate information into early warning systems or decision-support tools for climate-sensitive sectors such as agriculture, water resources, health, and disaster preparedness.
- Experience working with climate systems and hazard contexts in Southeast Asia and/or South Asia.
- Personal Attributes.
- Strategic thinker with strong analytical and solution-oriented capabilities in applied climate science.
- Self-driven and capable of working independently while maintaining accountability and initiative.
- Effective collaborator with the ability to work in multicultural, interdisciplinary teams and manage cross-sectoral engagement.
- Detail-oriented and results-focused, with adaptability in dynamic and evolving operational environments.
- Professional, respectful, and proactive in both independent and team-based work settings.
- Major Duties and Responsibilities.
- Lead the development and delivery of climate-related products and services under the Decision Support System (DSS), including seasonal and sub-seasonal forecasts, bulletins, and outlooks.
- Design scalable climate analysis tools and frameworks for integration into RIMES DSS across countries and projects.
- Analyze historical and real-time climate data to identify trends, anomalies, thresholds, and risks.
- Manage and apply climate datasets, assimilation data, and remote sensing for climate analysis and risk assessment.
- Develop and implement bias correction and error adjustment methods, including statistical and machine learning techniques, to enhance forecast accuracy.
- Integrate climate information into sector-specific early warning systems and planning processes across agriculture, water, health, and disaster risk management.
- Provide technical support and capacity strengthening to national and regional partners on climate data analysis, modeling, and application.
- Design and conduct trainings, workshops, and technical mentoring; produce manuals, guidance notes, and documentation to ensure sustainability and knowledge transfer.
- Collaborate across RIMES thematic teams to develop integrated, impact-based climate advisories and contribute to cross-sectoral resilience programming.
- Represent RIMES in technical forums, support resource mobilization, and maintain active engagement with meteorological agencies, donors, and development partners.
- Contribute to the design, testing, and documentation of forecasting tools and services, as well as to the preparation of reports, proposals, and related documentation.
- Perform other duties as assigned to support RIMES climate-related programs and institutional objectives.
- Contract Duration.
- The contract will initially be for one year and may be extended based on the satisfactory completion of a 180-day probationary period and subsequent annual performance reviews.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
5 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Git, Python, R, TensorFlow, GIS, Thai, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
- A Bachelor s degree in Data Science, Computer Science, Geoinformatics, Statistics, Earth Sciences, or a related field, with a minimum of five (5) years of relevant professional experience in data science, preferably in geospatial or geophysical applications;.
- A Master s degree in related field with at least three (3) years of relevant experience.
- Strong proficiency in Python or R, with experience using data analytics libraries (e ...
- Solid understanding of machine learning concepts, time-series analysis, and statistical modeling.
- Familiarity with geospatial data formats (e.g., NetCDF, GRIB, GeoTIFF) and GIS tools is a plus.
- Familiarity with global and regional forecasting systems and platforms and experience working with climate datasets.
- Strong analytical, diagnostic, and systems-level problem-solving skills.
- Proven ability to interpret and communicate complex scientific findings to technical and non-technical audiences, including policy- and decision-makers.
- Ability to document technical work and communicate findings clearly with the project team.
- Capacity to manage multiple assignments under tight deadlines and work effectively in a cross-disciplinary, multicultural team environment.
- Minimum 3 years of experience in data science, preferably in geospatial or geophysical applications.
- Experience working with scientific computing and version control systems (e.g., Git).
- Personal Qualities.
- Conscientious and efficient in meeting commitments, observing deadlines, and achieving results.
- Self-driven and capable of working independently while maintaining accountability and initiative.
- Effective collaborator with the ability to work in multicultural, interdisciplinary teams and manage cross-sectoral engagement.
- Detail-oriented and results-focused, with adaptability in dynamic and evolving operational environments.
- Professional, respectful, and proactive in both independent and team-based work settings.
- Major Duties and Responsibilities.
- Collect, organize, and maintain large-scale structured and unstructured datasets from seismic, oceanographic, observational sources, and historical records.
- Contribute to the design and development of the tsunami scenario database, including data indexing, tagging, and retrieval functionality.
- Conduct exploratory data analysis (EDA) to identify trends, anomalies, and features relevant to support scenario-based modeling.
- Model Development.
- Collaborate with system architects and software developers to integrate data science models into the PRECISE platform.
- Develop probabilistic models to quantify uncertainty in tsunami impact forecasts, including scenario-based risk assessments and ensemble modeling techniques.
- Develop statistical and ML models to identify patterns, anomalies, and predictive signals for tsunami generation and propagation.
- Evaluate model performance and implement optimization strategies to improve prediction accuracy and computational efficiency.
- Document data sources, methodologies, models, and workflows to ensure reproducibility and transparency.
- Provide technical recommendations for future AI/ML tool integration based on findings and emerging trends.
- Other tasks.
- Support the development of visualization tools and dashboards for real-time data interpretation and communication with end users.
- Collaborate with cross-functional teams including researchers, domain experts, and developers to ensure effective system design and integration.
- Provide technical support and documentation, including system manuals, deployment instructions, and maintenance guidelines.
- Perform other duties as may be required by the Project Lead.
- Contract Duration.
- The contract will initially be for one year and may be extended based on the satisfactory completion of a 180-day probationary period and subsequent annual performance reviews..
- RIMES promotes diversity and inclusion in the workplace. Well-qualified applicants particularly women are encouraged to apply..
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āļŦāļēāļāļēāļāļāđāļēāļ WorkVenture āđāļāđāļāļĒāđāļēāļāđāļĢ?
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