About The Role
The role drives the development of advanced predictive models and statistical analyses that directly inform product strategy and business decisions. This position sits at the intersection of causal inference, experimental design, and machine learning, translating complex behavioral data into actionable insights.
The team focuses on building scalable data products and analytical frameworks. The incoming Data Scientist will collaborate closely with product managers, data engineers, and business leaders to define key metrics, design robust A/B tests, and deploy predictive models to production.
Key Responsibilities
- Design, execute, and analyze complex A/B and multivariate experiments to evaluate product feature launches and algorithm changes
- Develop, validate, and deploy predictive models using Python to forecast user behavior, lifetime value, and engagement metrics
- Build automated SQL pipelines and dashboards to monitor core business metrics, ensuring high data quality and consistency
- Perform deep-dive exploratory data analysis to identify product opportunities, user pain points, and growth levers
- Formulate causal inference frameworks to measure the long-term impact of business initiatives when randomized control trials are not feasible
- Communicate complex statistical findings and strategic recommendations to both technical and non-technical stakeholders
What We Are Looking For
- 3–6 years of experience as a Data Scientist or Quantitative Analyst, preferably in a high-growth tech environment
- Expert-level proficiency in SQL and Python (including pandas, numpy, scikit-learn, and statsmodels)
- Strong theoretical and practical foundation in statistics, experimental design, hypothesis testing, and causal inference
- Experience building, evaluating, and deploying machine learning models to solve business classification and regression problems
- Master's or PhD in Statistics, Economics, Computer Science, or another quantitative field
- Bonus: Experience with Tableau or Looker, dbt for data transformation, and cloud platforms like Snowflake, BigQuery, or AWS
