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āļāļąāļāļĐāļ°:
Big Data, Hive, SAS
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- System Design: Knowledge of system design and platform thinking to build sustainable solutions.
- Big Data Experience: Practical experience with modern and traditional Big Data stacks (e.g., BigQuery, Spark, Databricks, duckDB, Impala, Hive).
- Data Warehouse Solutions: Experience working with data warehouse solutions, ELT tools, and techniques (e.g., Airflow, dbt, SAS, Nifi).
- API Development: Experience with API design to facilitate integration of LLMs with other systems.
- Prompt Engineering: Skills in designing sequential tasks for LLMs to achieve efficient and accurate outputs.
- Agile Methodologies: Experience with agile software delivery and CI/CD processes.
- Education: Bachelor's or Master's degree in Computer Science, AI, Engineering, or a related field.
- Experience: At least 3 years of experience in data engineering and modeling.
- Technical Skills: Proficiency in Python, experience with LLM frameworks (e.g., LangChain), and familiarity with cloud computing platforms.
- Cloud Computing: Familiarity with cloud computing platforms, such as GCP, AWS, or Databricks.
- Problem-Solving: Strong problem-solving skills with the ability to work independently and collaboratively.
- Growth Potential: This role offers a clear path to advance into AI engineering, providing opportunities to work on innovative projects and develop new skills in AI transformation and machine learning..
- You have read and reviewed Infinitas By Krungthai Company Limited's Privacy Policy at https://krungthai.com/Download/download/DownloadDownload_73Privacy_Policy_Infinitas.pdf. 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°:
Big Data, Hive, SAS
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Experience migrating from on-premise data stores to cloud solutions.
- Knowledge of system design and platform thinking to build sustainable solution.
- Practical experience with modern and traditional Big Data stacks (e.g BigQuery, Spark, Databricks, duckDB, Impala, Hive, etc).
- Experience working with data warehouse solutions ELT solutions, tools, and techniques (e.g. Airflow, dbt, SAS, Matillion, Nifi).
- Experience with agile software delivery and CI/CD processes.
- Bachelor's or Master's degree in computer science, statistics, engineering, or a related field.
- At least 3 years of experience in data analysis and modeling.
- Proficiency in Python, and SQL.
- Experience with data visualization tools such as Tableau, Grafana or similar.
- Familiarity with cloud computing platforms, such as GCP, AWS or Databricks.
- Strong problem-solving skills and the ability to work independently as well as collaboratively.
- Growth Potential: This role offers a clear path to advance into machine learning and AI with data quality and management, providing opportunities to work on innovative projects and develop new skills in these exciting fields..
- Contact: [email protected].
- You have read and reviewed Infinitas By Krungthai Company Limited's Privacy Policy at https://krungthai.com/Download/download/DownloadDownload_73Privacy_Policy_Infinitas.pdf. 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.".
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
2 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Research, Python, SQL
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Develop machine learning models such as credit model, income estimation model and fraud model.
- Research on cutting-edge technology to enhance existing model performance.
- Explore and conduct feature engineering on existing data set (telco data, retail store data, loan approval data).
- Develop sentimental analysis model in order to support collection strategy.
- Bachelor Degree in Computer Science, Operations Research, Engineering, or related quantitative discipline.
- 2-5 years of experiences in programming languages such as Python, SQL or Scala.
- 5+ years of hands-on experience in building & implementing AI/ML solutions for senior role.
- Experience with python libraries - Numpy, scikit-learn, OpenCV, Tensorflow, Pytorch, Flask, Django.
- Experience with source version control (Git, Bitbucket).
- Proven knowledge on Rest API, Docker, Google Big Query, VScode.
- Strong analytical skills and data-driven thinking.
- Strong understanding of quantitative analysis methods in relation to financial institutions.
- Ability to clearly communicate modeling results to a wide range of audiences.
- Nice to have.
- Experience in image processing or natural language processing (NLP).
- Solid understanding in collection model.
- Familiar with MLOps concepts.
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļāļģāđāļŦāļāđāļ āļĢāļāļāļāļđāđāļāļģāļāļ§āļĒāļāļēāļĢāļāđāļēāļĒ (VP) āđāļĨāļ°āļŦāļąāļ§āļŦāļāđāļēāļŠāđāļ§āļ (AVP).
- āļŦāļāđāļēāļāļĩāđāļāļ§āļēāļĄāļĢāļąāļāļāļīāļāļāļāļāļāļēāļāļĢāļ°āļāļāļāļĢāļīāļŦāļēāļĢāļŠāļīāļāđāļāļ·āđāļ (Loan Origination)
- āđāļāđāļāļĻāļđāļāļĒāđāļāļĨāļēāļāļāļąāļāļāļēāđāļĨāļ°āļāļīāļāļāļēāļĄāļāļēāļĢāđāļāđāļāļēāļāļĢāļ°āļāļāļāļĢāļīāļŦāļēāļĢāļŠāļīāļāđāļāļ·āđāļ āļĢāļ§āļĄāļāļąāđāļāļāļģāļŦāļāļāļŠāļīāļāļāļīāđāđāļĨāļ°āļĢāļ°āļāļąāļāļāļēāļĢāđāļāđāļēāđāļāđāļāļēāļāļĢāļ°āļāļ
- āļāļĢāļ°āļŠāļēāļāļāļēāļāļĢāļ°āļŦāļ§āđāļēāļāļāļđāđāđāļāđ āđāļĨāļ°āļŦāļāđāļ§āļĒāļāļēāļ IT āđāļāļ·āđāļāđāļŦāđāļāļēāļĢāļŠāļāļąāļāļŠāļāļļāļāļāļļāļāļāđāļēāļāđāļāļĩāđāļĒāļ§āļāļąāļāļāļēāļĢāđāļāđāļāļēāļāļĢāļ°āļāļ āļāļĨāļāļāļāļāļāļēāļĢāļāļĢāļąāļāļāļĢāļļāļāđāļāđāđāļāļĢāļ°āļāļāļāļēāļ
- āļāļģāļŦāļāļ āđāļĨāļ°āļĢāļ§āļāļĢāļ§āļĄāļĢāļ°āđāļāļĩāļĒāļāļāļēāļĢāļāļāļīāļāļąāļāļīāļāļēāļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ āđāļāļ·āđāļāļāđāļēāļāļāļīāļ āđāļĨāļ°āļāļĢāļąāļāļāļĢāļļāļāđāļāđāđāļāđāļŦāđāđāļāđāļāļāļąāļāļāļļāļāļąāļāļāļĒāļđāđāđāļŠāļĄāļ
- āļāļ§āļāļāļļāļĄāļāļđāđāļĨāļāļđāđāđāļāđāļĢāļ°āļāļ āđāļĨāļ°āļāļģāļŦāļāļāļĄāļēāļāļĢāļāļēāļāļāļēāļĢāļāļąāļāļāļķāļāļāđāļāļĄāļđāļĨāđāļāļĢāļ°āļāļāļāļēāļāđāļŦāđāļāļđāļāļāđāļāļ
- āļāļĢāļīāļŦāļēāļĢāļāđāļāļĄāļđāļĨāļāļĩāđāļĄāļĩāļāļĒāļđāđāđāļāļĢāļ°āļāļāđāļāļ·āđāļāļāļģāļĄāļēāđāļāđāđāļāđāļāļīāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđ āđāļĨāļ°āļŠāļĢāļļāļāļāļĨāļāļēāļ/āļĢāļēāļĒāļāļēāļāļāđāļēāļ āđ āļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāđāļŦāđāļāļąāļāļāļāļēāļāļēāļĢ
- āļāļēāļāļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāļāđāļāļĄāļđāļĨāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļāđāļēāļāļŠāļīāļāđāļāļ·āđāļ.
- āļŠāļĢāđāļēāļāđāļĨāļ°āļāļđāđāļĨāļāļąāļāļāļēāļĢ Data Pipeline Architecture āđāļŦāđāđāļāļīāļāļāļĢāļ°āđāļĒāļāļāđāļŠāļđāļāļŠāļļāļ
- āđāļŦāđ Requirement IT āļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļāļēāļāļĢāļ°āļāļāļāļēāļāļāđāļāļĄāļđāļĨāļāļāļāļāļāļēāļāļēāļĢāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāđāļĨāļ°āļĢāļ°āļāļāļāļēāļāļāđāļēāļāđāđāļāļ·āđāļāļāļąāļāļāļģ āđāļĨāļ°āļāļđāđāļĨ
- Datamart āđāļŦāđāļĄāļĩāļāđāļāļĄāļđāļĨāļāļĩāđāđāļāđāļāļāļąāļāļāļļāļāļąāļ āđāļĨāļ°āļŠāļĄāļāļđāļĢāļāđāļāļĢāđāļāļĄāđāļāđāļāļēāļ āđāļāđāļ āđāļāđāđāļāļāļēāļĢāļāļąāļāļāļē āļāļāļŠāļāļāđāļĨāļ°āļāļīāļāļāļēāļĄāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļāđāļāļāļāļģāļĨāļāļ āđāļĨāļ°āđāļāđāđāļāļāļēāļĢāļāļĢāļīāļŦāļēāļĢāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļŠāļīāļāđāļāļ·āđāļāļāļļāļĢāļāļīāļ
- āļāļĢāļ°āļĄāļ§āļĨāļāļĨāļāđāļāļĄāļđāļĨāđāļāļ·āđāļāđāļŦāđāļāđāļāļĄāļđāļĨāļŠāļēāļĄāļēāļĢāļāļāļģāđāļāđāļāđāđāļāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļāđāļēāļāļŠāļīāļāđāļāļ·āđāļāđāļĨāļ°āļāļąāļāļāļģāļĢāļēāļĒāļāļēāļ āļŠāđāļāļŦāļāđāļ§āļĒāļāļēāļāļāļ·āđāļ
- āļāļīāļāļāļēāļĄāđāļĨāļ°āļāļĢāļ°āđāļĄāļīāļāļāļļāļāļ āļēāļāļāļāļāļāđāļāļĄāļđāļĨāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļāđāļēāļāļŠāļīāļāđāļāļ·āđāļ āļĢāļ§āļĄāļāļąāđāļāļāļĢāļąāļāļāļĢāļļāļāļāļļāļāļ āļēāļāļāļāļāļāđāļāļĄāļđāļĨāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļāļąāļāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāđāļŦāđāļĄāļĩāļāļ§āļēāļĄāļāļđāļāļāđāļāļāļāđāļēāđāļāļ·āđāļāļāļ·āļ
- āļāļ§āļāļāļļāļĄāļāļđāđāļĨāļāļēāļĢāđāļāđāļāđāļāļĄāļđāļĨ āđāļĨāļ°āļŠāļīāļāļāļīāđāļāļēāļĢāđāļāđāļēāļāļķāļāļāļēāļĢāđāļāđāļāđāļāļĄāļđāļĨ (āđāļāļāļēāļ°āļĢāļ°āļāļāļāļēāļāđāļĨāļ° Datamart āļāļĩāđāļāđāļēāļĒāļŊ āđāļāđāļ owner)
- āļāļąāļāļāļģāļāļđāđāļĄāļ·āļāļĄāļēāļāļĢāļāļēāļāļāļēāļĢāļāļāļīāļāļąāļāļīāļāļēāļ (SOP) āđāļĨāļ°āļāļđāđāļĄāļ·āļāļāļēāļĢāļāļāļīāļāļąāļāļīāļāļēāļ (User Manual) āļāļāļāļŦāļāđāļ§āļĒāļāļēāļ
- āļāļāļīāļāļąāļāļīāļŦāļāđāļēāļāļĩāđāļāđāļēāļāļāļēāļĢāļāļāļąāļāļāļ āđāļĨāļ°āļāļķāļāļāļāļĢāļĄ āļāļāļāļĢāļ°āļĄāļēāļ āļāđāļēāđāļāđāļāđāļēāļĒ āļŠāļēāļĢāļāļĢāļĢāļ āđāļĨāļ°āļĢāļ§āļāļĢāļ§āļĄāđāļāļāļāļēāļĢāļāļģāđāļāļīāļāļāļēāļāļāļāļāļŦāļāđāļ§āļĒāļāļēāļ
- āļāļāļīāļāļąāļāļīāļŦāļāđāļēāļāļĩāđāļāļ·āđāļāđāļāļāļēāļĄāļāļĩāđāđāļāđāļĢāļąāļāļĄāļāļāļŦāļĄāļēāļĒ
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāđāļāļāļēāļĢāđāļāļāļēāļāļāđāļēāļ Project Management
- āļĄāļĩāļāļ§āļēāļĄāļĢāļđāđāđāļĨāļ°āļāļ§āļēāļĄāđāļāđāļēāđāļāļāđāļēāļāļŠāļīāļāđāļāļ·āđāļāļāļļāļĢāļāļīāļāļāļāļēāļāđāļŦāļāđ
- āļĄāļĩāļāļ§āļēāļĄāļĢāļđāđāļāļĩāđāļāļģāđāļāđāļāļāđāļ model development āđāļĨāļ° maintenance āđāļāđāđāļāđ āļāļ§āļēāļĄāļĢāļđāđāđāļāļĩāđāļĒāļ§āļāļąāļāļāļēāļĢāļāļąāļāļāļēāđāļāļāļāļģāļĨāļāļāđāļĨāļ°āļŠāļāļīāļāļī (Modelling, Statistics) āļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāđāļāļĄāļđāļĨāļāļāļēāļāđāļŦāļāđ (Data Analytics, Big Data) āđāļĨāļ° computer programming (e.g. Data Science) āđāļĨāļ°āļĄāļĩāļāļ§āļēāļĄāļĢāļđāđāļāļĒāđāļēāļāļāđāļāļĒāļāļĒāđāļēāļāđāļāļāļĒāđāļēāļāļŦāļāļķāđāļ āļāđāļāđāļāļāļĩāđ āđāļāđāļ āđāļāļāļāļģāļĨāļāļāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļāđāļēāļāļŠāļīāļāđāļāļ·āđāļ (Credit Risk Modelling, IFRS9, Basel, Credit Rating, Credit Pricing Model) āļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāđāļāļĄāļđāļĨāļāđāļēāļāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļŠāļīāļāđāļāļ·āđāļ (Credit Risk Analysis)āļāļ§āļēāļĄāļĢāļđāđāļāļēāļāļāđāļēāļāđāļĻāļĢāļĐāļāļĻāļēāļŠāļāļĢāđāļāļēāļĢāđāļāļīāļāđāļĨāļ°āđāļĻāļĢāļĐāļāļāļīāļāļĄāļŦāļ āļēāļ āđāļĨāļ°āļāļēāļĢāļāļąāļāļāļēāļĢāļāđāļāļĄāļđāļĨ (MIS, Data
- Engineering)
- āļĄāļĩāļ§āļļāļāļīāļāļēāļĢāļĻāļķāļāļĐāļēāļĢāļ°āļāļąāļāļāļĢāļīāļāļāļēāđāļāļāļķāđāļāđāļ āļāđāļēāļ Statistics, Econometrics, Data Science, Data Analytics, Computer Science, Computer Engineering, Operational Research, Risk Analytics/Modelling, Mathematical Finance, Financial Engineering, Economics, MIS āļŦāļĢāļ·āļāļŠāļēāļāļēāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ
- āļāļąāļāļĐāļ°āļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļāļāļīāđāļĻāļĐāļāļ·āđāļ āđ
- āļĄāļĩāļāļąāļāļĐāļ°āļ āļēāļĐāļēāļāļąāļāļāļĪāļĐāđāļāļĢāļ°āļāļąāļāļāļĩāļŦāļĢāļ·āļāļāļĩāļĄāļēāļ
- āļĄāļĩāļāļąāļāļĐāļ°āļāļēāļĢāļāļģāļāļēāļāđāļāđāļāļāļĩāļĄāđāļĨāļ°āļāļąāļāļĐāļ°āļāļēāļĢāļŠāļ·āđāļāļŠāļēāļĢ āļĢāļ§āļĄāļāļķāļāļāļēāļĢāļāļģāđāļŠāļāļāļāļĨāļāļēāļāļāļĩāđāļāļĩ
- āļĄāļĩāļāļąāļāļĐāļ°āļāļēāļāļāļāļĄāļāļīāļ§āđāļāļāļĢāđ āļŠāļēāļĄāļēāļĢāļāđāļāđāļāļāļĄāļāļīāļ§āđāļāļāļĢāđāđāļāđāđāļāđāļāļāļĒāđāļēāļāļāļĩ āđāļāđāļ āđāļāļĢāđāļāļĢāļĄ SAS, SQL, Machine Learning, Deep Learning, MS āđāļāļīāļāļĨāļķāļ āđāļĨāļ° Python āđāļāđāļāļāđāļ āđāļĨāļ°āļŠāļēāļĄāļēāļĢāļāļŠāļĢāđāļēāļāđāļĨāļ°āļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāļāļēāļāļāđāļāļĄāļđāļĨāđāļāđāļāļĒāđāļēāļāļĄāļĩāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļ.
- 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°:
Data Analysis, Finance, SQL, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Data Analysis: Conduct in-depth analysis of retail and wholesale business data to address specific business questions and challenges.
- Insight Generation: Interpret results from dashboards and data analyses to develop actionable insights and strategic recommendations.
- Requirement Gathering: Identify business problems, gather requirements, and propose potential solutions, including leveraging AI to enhance business operations.
- ML Model creation: Create data analytic model including both deterministic and machine learning model.
- AI vendors coordination: Collaborate with external AI suppliers to align project objectives with technological capabilities.
- Cross-Departmental Collaboration: Work with various departments to develop and implement data-driven strategies that optimize business processes and decision-making.
- Communication: Act as a liaison between stakeholders and AI vendors, ensuring clear communication and understanding of project requirements.
- Data analytics and AI Strategy Design: Design and recommend how Business Intelligence (BI) and AI technologies can address business problems and provide further insights.
- Decision-making support: Present key findings from own analysis and strategic recommendations to business counterparts and senior management, focusing on project approaches and strategic planning.
- Master's degree in Finance, Business, Engineering, or a related field.
- Strong business acumen, with a deep understanding of retail and wholesale business.
- 3+ years of proven experience as a data analytic role (Retail or E-Commerce business is preferable).
- Hands-on Experience in SQL, data cloud platform (e.g., Databricks, Snowflake, GCP, or AWS), and high proficiency in Excel.
- Good Knowledge of Statistics.
- Experience in Python (Pandas, Numpy, SparkSQL), Data Visualisation (Tableau, PowerBI) is a plus.
- Excellent communication skills with the ability to convey complex findings to non-technical stakeholders.
- Fluent in Thai and English.
- Having a good attitude toward teamwork and willing to work hard.
- CP AXTRA | Lotus's
- CP AXTRA Public Company Limited.
- Nawamin Office: Buengkum, Bangkok 10230, Thailand.
- By applying for this position, you consent to the collection, use and disclosure of your personal data to us, our recruitment firms and all relevant third parties for the purpose of processing your application for this job position (or any other suitable positions within Lotus's and its subsidiaries, if any). You understand and acknowledge that your personal data will be processed in accordance with the law and our policy. .
āļāļąāļāļĐāļ°:
Research
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Design, develop, and implement AI/ML solutions, including Generative AI models, deep learning, neural networks, and chatbots.
- Build scalable and optimized AI pipelines for cloud or on-premises environments.
- Collaborate with cross-functional teams to integrate AI solutions into business applications.
- Provide technical leadership and guide the team in adopting AI best practices.
- Research and implement cutting-edge AI technologies to enhance project outcomes.
- Conduct regular knowledge-sharing sessions to improve team capabilities.
- Stay updated on the latest AI trends and advancements.
- Expert proficiency in Generative AI and strong experience in Machine Learning.
- Solid understanding of Data Architecture Principles.
- Experience with Platform Engineering and cloud-based AI services.
- Strong problem-solving skills and ability to provide scalable AI solutions.
- Experience working in Customer Services in Retail industry is advantage.
- Ability to collaborate across teams and lead AI initiatives.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
5 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
ETL, Quantitative Analysis, Industry trends
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Translating business requirements to technical solutions leveraging strong business acumen.
- You will be a core member of the EY Microsoft Data and AI team, responsible for extracting large quantities of data from client s IT systems, developing efficient ETL and data management processes, and building architectures for rapid ingestion and dissemination of key data.
- Apply expertise in quantitative analysis, data mining and presentation of data to de ...
- Extremely flexible and experience managing multiple tasks and priorities on deadlines.
- Applying technical knowledge to architect solutions that meet business and IT needs, create Data Platform roadmaps, and enable the Data Platforms to scale to support additional use cases.
- Staying abreast of current business and industry trends relevant to the client's business.
- Monitoring progress, managing risk, and ensuring key stakeholders are kept informed about progress and expected outcomes.
- Understanding customers overall data estate, IT and business priorities and success measures to design implementation architectures and solutions.
- Strong team collaboration and experience working with remote teams.
- Working on large-scale client engagements. Fostering relationships with client personnel at appropriate levels. Consistently delivering quality client services. Driving high-quality work products within expected timeframes and on budget.
- Demonstrated significant professional experience of commercial, strategy and/or research/analytics interacting with senior stakeholders to effectively communicate insights.
- Execute on building data solutions for business intelligence and assist in effectively managing and monitoring the data ecosystem of analytics, data lakes, warehouses platforms and tools.
- Provide directional guidance and recommendations around data flows including data technology, data integrations, data models, and data storage formats.
- To qualify for the role, you must have.
- Bachelor s degree, or MS degree in Business, Economics, Technology Entrepreneurship, Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning.
- Minimum of 3-5 years of relevant consulting experience with focus on advanced analytics and business intelligence or similar roles. New graduated are welcome!.
- Communication and critical thinking are essential, must be able to listen and understand the question and develop and deliver clear insights.
- Experience communicating the results of analysis to both technical and non-technical audiences.
- Independent and able to manage and prioritize workload.
- Ability to adapt quickly and positively to change.
- Breadth of technical passion, desire to learn and knowledge services.
- Willingness and ability to travel to meet client if need.
- Ideally, you ll also have.
- Experience working business or IT transformation projects that have supported data science, business intelligence, artificial intelligence, and cloud applications at scale.
- Ability to communicate clearly and succinctly, adjusts to a variety of styles and audiences with ability to tell compelling stories with the data.
- Experience with C#, VBA, JavaScript, R.
- A vast understanding of key BI trends and the BI vendor landscape.
- Working experience with Agile and/or Scrum methods of delivery.
- Working experience with design led thinking.
- Microsoft Certifications in the Data & AI domain.
- We re interested in passionate leaders with strong vision and a desire to deeply understand the trends at the intersection of business and Data and AI. We want a customer-focused professional who is motivated to drive the creation of great enterprise products and who can collaborate and partner with other product teams, and engineers. If you have a genuine passion for helping businesses achieve the full potential of their data, this role is for you.
- What we offer.
- We offer a competitive compensation package where you ll be rewarded based on your performance and recognized for the value you bring to our business. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options. Under our flexible vacation policy, you ll decide how much vacation time you need based on your own personal circumstances. You ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
- Continuous learning: You ll develop the mindset and skills to navigate whatever comes next.
- Success as defined by you: We ll provide the tools and flexibility, so you can make a meaningful impact, your way.
- Transformative leadership: We ll give you the insights, coaching and confidence to be the leader the world needs.
- Diverse and inclusive culture: You ll be embraced for who you are and empowered to use your voice to help others find theirs.
- If you can demonstrate that you meet the criteria above, please contact us as soon as possible.
- The exceptional EY experience. It s yours to build.
- EY | Building a better working world.
- EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
- Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
- Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.
- EY is an equal opportunity, affirmative action employer providing equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, national origin, protected veteran status, disability status, or any other legally protected basis, in accordance with applicable law.
āļāļąāļāļĐāļ°:
Big Data, ETL, SQL
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Develop and maintain robust data pipelines to ingest, process, and transform raw data into formats suitable for LLM training.
- Conduct meeting with users to understand the data requirements and perform database design based on data understanding and requirements with consideration for performance.
- Maintain data dictionary, relationship and its interpretation.
- Analyze problem and find resolution, as well as work closely with administrators to monitor performance and advise any necessary infrastructure changes.
- Work with business domain experts, data scientists and application developers to identify data that is relevant for analysis.
- Develop big data solutions for batch processing and near real-time streaming.
- Own end-to-end data ETL/ELT process framework from Data Source to Data warehouse.
- Select and integrate appropriate tools and frameworks required to provide requested capabilities.
- Design and develop BI solutions.
- Hands-on development mentality, with a willingness to troubleshoot and solve complex problems.
- Keep abreast of new developments in the big data ecosystem and learn new technologies.
- Ability to effectively work independently and handle multiple priorities.
- Bachelor degree or higher in Computer Science, Computer Engineering, Information Technology, Management Information System or an IT related field.
- 3+ year's experiences in Data Management or Data Engineer (Retail or E-Commerce business is preferrable).
- Expert experience in query language (SQL), Databrick SQL, PostgreSQL.
- Experience in Big Data Technologies like Hadoop, Apache Spark, Databrick.
- Experience in Python is a must.
- Experience in Generative AI is a must.
- Knowledge in machine/statistical learning, data mining is a plus.
- Strong analytical, problem solving, communication and interpersonal skills.
- Having good attitude toward team working and willing to work hard.
- CP AXTRA | Lotus's
- CP AXTRA Public Company Limited.
- Nawamin Office: Buengkum, Bangkok 10230, Thailand.
- By applying for this position, you consent to the collection, use and disclosure of your personal data to us, our recruitment firms and all relevant third parties for the purpose of processing your application for this job position (or any other suitable positions within Lotus's and its subsidiaries, if any). You understand and acknowledge that your personal data will be processed in accordance with the law and our policy. .
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
8 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Data Analysis, Tableau, Excel
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Work closely with stakeholders to understand business requirements, identify opportunities, and whitespace to commercialize data-driven insights and solutions.
- The candidate will need to lead data analysis and sales pitching for the Annual Media planning process, and have good commercial awareness and communication skills to be able to connect with multiple stakeholders.
- Break down business questions into analytical frameworks, and being able to talk the language of technical teams as well as commercial stakeholders is a key requirement ...
- The candidate will need to lead the development of end-to-end data lead media solutions, and media measurements to keep ahead of the media industry standards and own roadmap to deploy and modernize media measurements across different media platforms, channels, and mechanics.
- Candidates should have some idea of offline and online SSP and DSP platforms and architecture, and market direction to strategically build and improve media solutions, either owned or in partnership with external parties.
- Be proactive and co-own the go to market strategy along with commercial stakeholders for multiple media channels/ and other data commercialization initiatives, and proactively help plan the right focus areas for the team, develop solutions and products to help build the roadmap and pipeline for commercial opportunities.
- Develop and implement predictive models, statistical algorithms, and machine learning models to support business needs.
- Develop and implement data visualizations using PowerBI/ Data Studio/QuickSight/ Tableau/ Excel to effectively communicate insights to stakeholders.
- Collaborate with cross-functional teams, including business analysts, product managers, and developers, to implement data-driven solutions.
- Stay up to date with emerging technologies, marketing technology platforms, omni-channel media and industry trends to identify new opportunities for improving data analytics and applications.
- Mentor and coach junior data scientists and data analysts to develop their skills and expertise.
- Bachelor s or Master s degree in data science/ engineering/ statistics/economics/ computer science/ mathematics, or a related field is a requirement.
- MBA/Business degree with strong background in technical understanding and hands-on expertise is preferable.
- Online media experience will be a strong advantage.
- 8+ years of experience as a data scientist or data analyst in marketing across any industry is a requirement.
- Strong proficiency in Python/ Pyspark/ SQL/ R is a requirement.
- Strong experience in story telling from data, analysis and insight is required.
- Commercial understanding, and having a balanced approach for go-to-market strategy is a requirement.
- Experience with machine learning algorithms and statistical modeling is a bonus.
- Strong communication skills and the ability to collaborate with cross-functional teams is a requirement.
- Proven ability to work independently and manage multiple projects simultaneously is a requirement.
- The candidate must display a high sense of accountability and be agile in handling high value projects, and be able to motivate the team to deliver as a shared objective with the commercial plan.
- Experience in mentoring and coaching junior/ senior DA/ DS is a requirement.
āļāļąāļāļĐāļ°:
ETL, Python, TensorFlow
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Develop and deploy machine learning models for demand forecasting, customer segmentation, pricing optimization, and inventory management.
- Work with large-scale datasets and implement efficient feature engineering pipelines to enhance model performance.
- Use PySpark to process and analyze large datasets in a distributed computing environment.
- Collaborate with data engineers to build scalable data pipelines and ensure data quality.
- Implement MLOps best practices for model deployment, monitoring, and retraining in production.
- Design ETL workflows for preprocessing and transforming structured and unstructured data.
- Communicate findings and recommendations to business stakeholders in a clear and actionable manner.
- Stay up to date with the latest advancements in AI, machine learning, and data engineering.
- 5+ years of experience in data science, machine learning, or applied AI.
- Strong programming skills in Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch).
- Hands-on experience with PySpark for big data processing and analysis.
- Experience with SQL for querying large datasets efficiently.
- Familiarity with cloud platforms (AWS, GCP, Azure) and distributed computing frameworks.
- Knowledge of MLOps practices (model versioning, CI/CD for ML, monitoring, automation).
- Experience working with ETL workflows and data engineering pipelines.
- Strong understanding of statistical analysis, time-series forecasting, and clustering techniques.
- Excellent problem-solving and communication skills, with the ability to translate data insights into business value.
- Experience in the retail industry or working with e-commerce/consumer data.
- Familiarity with tools like Databricks, Airflow, MLflow, and Docker/Kubernetes.
- Experience with deep learning frameworks for NLP or computer vision.
- CP AXTRA | Lotus's
- CP AXTRA Public Company Limited.
- Nawamin Office: Buengkum, Bangkok 10230, Thailand.
- By applying for this position, you consent to the collection, use and disclosure of your personal data to us, our recruitment firms and all relevant third parties for the purpose of processing your application for this job position (or any other suitable positions within Lotus's and its subsidiaries, if any). You understand and acknowledge that your personal data will be processed in accordance with the law and our policy. .
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
5 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Product Owner, Product Development, CFA
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Customer-Centric Design: Champion a customer-first approach, ensuring our investment products deliver intuitive, seamless, and delightful user experiences.
- Data-Driven Decision Making: Utilize data insights to inform product decisions, prioritize features, and measure success against key performance indicators.
- AI-Powered Innovation: Leverage AI and machine learning to analyze user behavior, identify trends, and uncover opportunities for product enhancement and personalization.
- Product Leadership: Define the product vision, strategy, and roadmap for your portfolio, aligning cross-functional teams and stakeholders towards a common goal.
- End-to-End Ownership: Manage the entire product lifecycle, from ideation and concept development to launch, iteration, and continuous improvement.
- Technical Collaboration: Partner effectively with engineering, design, and data science teams, translating business requirements into technical specifications and ensuring successful implementation.
- 5+ years of experience as a Product Manager, Product Owner, or similar role in fintech, investment management, or a related field.
- Proven track record of delivering successful investment or wealth management products with measurable impact on customer satisfaction and business outcomes.
- Strong analytical skills with the ability to interpret complex data and derive actionable insights.
- Experience with AI/ML techniques and their application in product development.
- Exceptional communication and presentation skills, capable of influencing and inspiring stakeholders at all levels.
- Experience working in agile environments and familiarity with tools like Jira.
- Passion for fintech and a deep understanding of the investment landscape.
- Nice to have.
- MBA or advanced degree in a relevant field.
- Experience in a startup or high-growth environment.
- CFA or other relevant financial certifications.
- Proficiency in SQL and data visualization tools.
āļāļąāļāļĐāļ°:
Research, Statistics, Python, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Apply statistical and machine learning methods to large, complex data sets to draw insights and provide actionable recommendations.
- Solve complex problems on both technical and business sides using advanced analytical methods.
- Work with Engineering teams to implement end-to-end process from model development to testing, validation, and deployment.
- Research and develop new quantitative models and frameworks to enhance the company s data science capability.
- Basic Qualifications Bachelor s degree in Engineering, Computer Science, Math, Physics, Statistics or other areas that are highly quantitative.
- Experience with statistical programming languages (e.g., Python, R, pandas) and database software (e.g., SQL, PySpark).
- Knowledge in statistics (e.g., hypothesis testing, regression) and machine learning.
- Strong analytical problem-solving capabilities.
- Preferred Qualifications Master s or PhD degree in a quantitative discipline.
- Experience applying machine learning and statistical methods to large datasets.
- Solid understanding of advanced statistics and machine learning practices.
- Experience in one or more specialized machine learning areas (e.g., NLP, deep learning, recommendation systems, reinforcement learning).
- Outstanding coding skills or software development background.
- Ability to think independently and communicate complex ideas to less technical persons.
- Excellent command of English in both verbal and written forms.
- We're committed to bringing passion and customer focus to the business. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us.
āļāļąāļāļĐāļ°:
Product Development, Product Design, Compliance, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Identify Investment Opportunities: monitor and analyze financial market trends using technical and quantitative methods to uncover timely, strategic investment opportunities aligned with organizational objectives and client needs.
- Develop Strategic Investment Insights: Create and present tailored investment ideas to internal stakeholders and for public communication to support informed decision-making and enhance market credibility.
- Data Management & Analysis: Maintain and optimize financial databases to ensure data ...
- Product Selection & Evaluation: Conduct in-depth, data-driven product evaluations using quantitative metrics to recommend high-performing financial products that support strategic goals.
- Leverage AI for Productivity & Insight: Design and implement AI-driven tools to automate tasks, streamline workflows, and enhance investment analysis, generating actionable insights to support strategic initiatives.
- Qualification Bachelor s degree or higher in Finance, Economics, Data Science, Engineering, or a related field.
- Strong financial expertise with demonstrated experience in investment analysis, product evaluation, and a deep understanding of financial markets, investment products, and portfolio strategies.
- Advanced analytical and technical skills, including proficiency in quantitative modeling, data analysis tools (e.g., Python, R, SQL, Excel), and handling large datasets. Familiarity with AI or machine learning is a plus.
- Excellent analytical, problem-solving and communication skills, with the ability to translate complex data into actionable investment insights.
- CMT, CFA, or other relevant certifications are a plus.
- Interested candidate, please submit your CV to [email protected] We're committed to bringing passion and customer focus to the business. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
1 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Finance, Statistics, Python, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Manage/ Clean/ Prepare internal and external data (structured/ semi-structured/ unstructured data) for model development/ deployment/ monitoring, including the production of data quality and integrity report.
- Develop statistical/ expert/ hybrid models to be able to enhance the model when model deterioration is indicated using variety of data modeling techniques such as Logistic Regression/ Random Forest/ Gradient Boosting/ Non-Parametric Regression. Also, in case of using external consultants, be able to work closely with them across all m ...
- Generate prescriptive models to respond to interactive decision to optimize risks and rewards.
- Deploy credit risk models into Databricks platform, collection system and credit decision engine and maintain any model adjustment.
- Assist and work closely with related parties, e.g. business users, credit approval officers and relationship managers to ensure credit risk models are appropriate and efficient for business direction and support for new digital lending risk assessment and platform.
- Ensure all credit risk models are qualified to be used through model life cycle. Regularly perform model monitoring, model assessment and propose proactive action/ recommendation to improve the model.
- Assist and design for business opportunity to develop alternative credit score from partnership data.
- Collaborate with IT and data engineer to ensure data availability and quality from various sources (both on-premise/ cloud) to develop an efficient model.
- Qualifications Bachelor s or higher degree in Finance, Statistics, Mathematics, Economics, MIS, Engineer, Data scientist or any related fields.
- At least 1-2 year experiences credit risk analytics, credit risk modeling/ scoring in retail banking, consumer finance or any financial business.
- Strong knowledge and skill in machine learning, credit scoring, data analytics using R/ Python/ PySpark, MATLAB, SPSS, SAS, SQL or similar required.
- Analytical mindset with excellent critical thinking ability and data analytics skills.
- Excellent computer skills and programming tools.
- Good command in both written and spoken English.
- Good project management skills.
- Good team player with a positive attitude toward hard working and working under pressure.
- Experienced in credit risk modeling, model monitoring/ validation/ deployment/ maintenance preferred.
- Prior experience in Basel/ IFRS9, RAROC, Stress Test, Big Data, Data Mining, Digital leading, Fin-tech/ Start-up is a plus.
- We're committed to bringing passion and customer focus to the business. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us.
- 1
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āļĨāļāļāļāļģ 5 āļŠāļīāđāļāļāļĩāđāļŦāļĨāļąāļāđāļĨāļīāļāļāļēāļ āļāļĩāļ§āļīāļāļāļļāļāļāļ°āđāļāļĨāļĩāđāļĒāļāđāļāļāļĨāļāļāļāļēāļĨ
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