Job Description - Business Intelligence Strategy : Develop and execute a comprehensive business intelligence strategy aligned with the company's goals and objectives. - Team Leadership : Lead and mentor a team of business analysts, data scientists, and data engineers to ensure the effective delivery of insights and analytics. - Data Collection and Integration : Oversee the collection, integration, and management of data from various sources, ensuring data accuracy and reliability. - Data Analysis : Utilize advanced analytics techniques to extract valuable insights from data, identifying trends, patterns, and opportunities for business improvement. - Reporting and Visualization : Create and maintain interactive dashboards and reports that provide stakeholders with real-time access to key performance indicators (KPIs) and actionable insights. - Data Governance : Establish and enforce data governance policies and standards to maintain data quality, security, and compliance with relevant regulations. - Strategic Planning : Collaborate with senior management to develop data-driven strategies for product development, marketing, sales, and operations. - Market Research : Conduct market research and competitive analysis to identify emerging trends and opportunities in the cosmetics industry. - Budget Management : Manage the department's budget, allocating resources efficiently to support business intelligence initiatives. - Stakeholder Communication : Effectively communicate insights and recommendations to executives and department heads, translating complex data into actionable insights. Qualifications 1. Bachelor's degree in business, data science, statistics, Industrial Engineering, or a related field (master's degree preferred). 2. Proven experience (8+ years) in business intelligence, data analysis, or related roles in project management and implementation, with at least 3 years in a leadership capacity. 3. Familiar with data analytics tools and technologies (e.g., SQL, Tableau, Power BI, Python). 4. Familiar with Project Management tools (e.g., Asana, Microsoft Planner) 5. In-depth knowledge of data analytics, data visualization and action plan implementation 6. Excellent problem-solving skills and the ability to think critically. 7. Strong communication and presentation skills. 8. Experience in the cosmetics industry or a FMCG industry is a plus. 9. Familiarity with regulatory requirements related to data privacy and security (e.g., PDPA) Location: Head Office Rama9 Soi53
āļāļąāļāļĐāļ°āļāļĩāđāļāļģāđāļāđāļ
- Industrial Engineering
- Product Development
- Project Management
- Market Research
- Data Analysis
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļĩāđāļāļģāđāļāđāļ
- 3 āļāļĩ
āđāļāļīāļāđāļāļ·āļāļ
- āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
āļŠāļēāļĒāļāļēāļ
- āļāļđāđāļāļĢāļīāļŦāļēāļĢāļāļēāļ§āļļāđāļŠ
- āđāļāļāļĩ / āđāļāļĩāļĒāļāđāļāļĢāđāļāļĢāļĄ
āļāļĢāļ°āđāļ āļāļāļēāļ
- āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļīāļĐāļąāļ
āļĻāļĢāļĩāļāļąāļāļāļĢāđ 73 āļāļĩāļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļāļāļĻāļĢāļĩāļāļąāļāļāļĢāđāļāļēāļāļāļāļĩāļāļāļāļāļķāļāļāļąāļāļāļļāļāļąāļ āđāļĄāđāļāļ°āđāļĄāđāđāļāđāļāļāļāđāļāļĢāļāļāļēāļāđāļŦāļāđ āđāļāđāļĻāļĢāļĩāļāļąāļāļāļĢāđāđāļāđāļāļāļāļāđāļāļĢāļāļĩāđāđāļāļ·āđāļāļĄāļąāđāļāđāļāļĻāļąāļāļĒāļ āļēāļāļāļāļāļāļĩāļĄāļāļēāļ āđāļĢāļēāđāļĨāļ·āļāļāļāļģāđāļāļŠāļīāđāļāļāļĩāđāđāļĢāļēāļāļāļąāļāđāļāļ·āđāļāļŠāļĢāđāļēāļāļŠāļĢāļĢāļāđāļŠāļīāđāļāļāļĩāđāļāļĩāļāļĩāđāļŠāļļāļ āđāļāļāļāļ°āđāļāļĩāļĒāļ§āļāļąāļāđāļĢāļēāļĒāļąāļāļāļāļāļąāļāļāļē āļāļĨāļīāļāļ āļąāļāļāđāđāļĨāļ°āļāļĢāļīāļāļēāļĢāļāļĒāđāļēāļāļŠāļĄāđāļģāđāļŠāļĄāļāđāļāļ·āđāļāļāļāļāđāļāļāļĒāđāļāļ§āļēāļĄāļāđāļāļāļāļēāļĢāļāļāļāļāļđāđāļāļĢāļīāđāļ āļāļāļĩāđāđāļāļĨāļĩāđ ... āļāđāļēāļāļāđāļ
āļĢāđāļ§āļĄāļāļēāļāļāļąāļāđāļĢāļē: āđāļĢāļēāļāļ°āđāļĄāđāļāļąāđāļāļāļģāļāļēāļĄāļ§āđāļē āļāļģāļāļĒāđāļēāļāđāļĢāļāļāđāļāļĒāļĄāļēāđāļāđāļŠāļīāļāļāđāļēāđāļāļĒ āđāļāđ "āļāļģāļāļāļ" āļāļāļāđāļĢāļē āļāļ·āļ āđāļĢāļēāļāļ°āļāļģāļŠāļīāļāļāđāļēāđāļŦāđāļāļĩāļāļĩāđāļŠāļļāļ āđāļĨāļ°āļāļģāđāļŦāđāļāļĩāļāļĩāđāļŠāļļāļāđāļāđāļĨāļ āđāļĨāļ° āļāļļāļāļĨāļēāļāļĢ āļāļāļąāļāļāļēāļāļāļāļāļĻāļĢāļĩāļāļąāļāļāļĢāđ āđāļāđāļāļŦāļąāļ§āđāļāļāļāļāļāļ§āļēāļĄāļŠāļģāđāļĢāđāļāļāļąāđāļ āļĻāļĢāļĩāļāļąāļāļāļĢāđāļāļģāļĨāļąāļāļĄāļāļāļŦāļēāļŠāļĄāļēāļāļīāļāļāļĩāļĄāļāļĩāđāļāļ°āļĄāļēāļĢāđāļ§āļĄāļāļļāļ āļĢāđāļ§āļĄāļĨāļļāļĒ āđāļĨāļ°āļŠāļĢāđāļēāļāđāļāļĢāļāļāđāđāļŦāđāđāļāļīāļāđāļāđāļāļāđāļ§āļĒāļāļąāļ āļŦāļēāļāļāļļāļāđāļāđāļāļāļāļāļĩāđāļāļāļāļāļ§āļēāļĄāļāđāļēāļāļēāļĒ āļāļāļāļ ... āļāđāļēāļāļāđāļ
āļŠāļ§āļąāļŠāļāļīāļāļēāļĢ
- āļāļģāļāļēāļ 5 āļ§āļąāļ/āļŠāļąāļāļāļēāļŦāđ
- āļāļāļāļāļļāļāļŠāļģāļĢāļāļāđāļĨāļĩāđāļĒāļāļāļĩāļ
- āļāļąāđāļ§āđāļĄāļāļāļģāļāļēāļāļĒāļ·āļāļŦāļĒāļļāđāļ
- āļāļļāļāļāļīāļāđāļāđāļāļĢāļēāļĒāđāļāļ·āļāļ
- āļāļĢāļ°āļāļąāļāļāļĩāļ§āļīāļ
- āļāļĢāļ°āļāļąāļāļŠāļąāļāļāļĄ
- āļāļķāļāļāļāļĢāļĄ
- āļāļĢāļ°āļāļąāļāļāļļāļāļąāļāļīāđāļŦāļāļļ
- āļĨāļēāļāļĨāļāļ
- āļŠāđāļ§āļāļĨāļāļāļāļąāļāļāļēāļ
- āđāļāļāļąāļŠāļāļķāđāļāļāļĒāļđāđāļāļąāļāļāļĨāļāļĢāļ°āļāļāļāļāļēāļĢ
- āđāļāļāļēāļŠāđāļāļāļēāļĢāđāļĢāļĩāļĒāļāļĢāļđāđāđāļĨāļ°āļāļąāļāļāļē
- āļŠāļĄāļēāļāļīāļāļāļīāļāđāļāļŠ
- āļāļģāļāļēāļāļāļāļāļŠāļāļēāļāļāļĩāđ

