Summary

WHAT YOU WILL DO

1. Deliver end-to-end data-driven product incubation by collaborating with Product Management to gather and prepare data/features, analyze data using programming/statistical languages (e.g., R, Python), generate insights, and select and deploy Machine Learning models to address business opportunities.
2. Interact cross-functionally and make business recommendations (e.g., cost-benefit, forecasting, experiment analysis) through effective presentation of findings to various stakeholder levels using clear data visualizations.
3. Conduct analysis including data gathering, requirement specification, data processing, ongoing reporting deliverables, and presentations.
4. Process, cleanse, and verify the integrity of data used for analysis.
5. Mine data to uncover important information and insights, and present results in a clear and concise manner.
6. Solve complex, non-routine analytical problems using advanced analytical methods as needed.
7. Build and prototype analytical pipelines iteratively to generate insights at scale.
8. Develop in-depth knowledge of the company’s data structures and metrics, and advocate for necessary changes to support product development.
9. Ensure strict adherence to development and quality standards.
10. Write clear and concise model documentation and support findings with sound reasoning.
11. Share best practices and case studies to help improve overall data literacy across the team.
12. Collaborate with Product Management and Engineering teams to drive product development.

REQUIREMENTS

1. Degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience.
2. 3–5 years of experience in analytics or a related field.
3. Strong expertise and hands-on experience in statistical analysis, machine learning modeling, and data visualization.
4. Demonstrated experience working with large and complex datasets.
5. Fluent in SQL, R, and Python.
6. Familiarity with BI tools such as Qlik, Tableau, and Metabase.
7. Demonstrated leadership and self-direction; willingness to teach others and learn new methods.
8. Experience with agile development methodology.
9. Effective written and verbal communication skills.

GOOD TO HAVE

1. Advanced degree in a quantitative discipline.
2. Specialized knowledge in time series analysis, deep learning, NLP, and graph analytics.
3. Experience in deploying machine learning models as cloud-native or containerized applications.
4. Proven experience or demonstrated capability in leveraging AI models to address real-world business challenges.

Skills

• Analytical Thinking
• Communications Skills
• Development
• Leadership
• Machine Learning
• Python
• Software Engineering
• SQL