Data Scientist Manager

Location: Bangkok, Bangkok, Thailand

Department: Technology

Workplace: on_site

Employment Type: full

Description

Data Strategy & Vision:

1. Define and implement a comprehensive data strategy for the Strategic Office Group, focusing on data collection, analysis, interpretation, and visualization to support business objectives.

Team Leadership & Development:

2. Build, mentor, and manage a team of data scientists and data analysts. Foster a collaborative environment that promotes skill development, knowledge sharing, and continuous improvement.

Analytical Solution Design:

3. Lead the design, development, and implementation of advanced analytical models, dashboards, and reports that provide actionable insights to stakeholders.

4. Oversee complex data exploration, statistical analysis, predictive modeling, and segmentation to identify trends, patterns, and opportunities.

Business Partnership:

5. Collaborate closely with various business units to understand their data needs, translate business questions into analytical problems, and deliver data-driven solutions.

Data Governance & Quality:

6. Work with data governance teams to ensure data quality, integrity, and compliance with internal policies and external regulations.

Tooling & Project Management::

7. Evaluate and recommend appropriate data analysis tools, platforms, and technologies to enhance the team's capabilities and efficiency.

8. Manage the lifecycle of data science and analytics projects, ensuring timely delivery, adherence to scope, and high-quality outputs.

Requirements

1. Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a related quantitative field.

2. Minimum of 5-8 years of progressive experience in data science, data analysis, or business intelligence, with at least 3-5 years in a leadership or management role.

3. Proven expertise in statistical analysis, predictive modeling, and data visualization techniques.

4. Strong proficiency in programming languages commonly used for data analysis (e.g., Python, R, SQL).

5. Extensive experience with data analysis and visualization tools (e.g., Tableau, Power BI, Looker, Excel).

6. Experience with big data technologies (e.g., Spark, Hadoop) and data warehousing solutions.

7. Solid understanding of database management systems and data manipulation.

8. Excellent analytical, problem-solving, and critical thinking skills.

9. Exceptional communication, presentation, and interpersonal skills, with the ability to translate complex data into clear business insights.