Senior Data Scientist, AI Product Insights
Tasks
- Apply causal inference methods to identify behavior drivers
- Assess data quality for forecasting and predictive features
- Build and own time series forecasting models
- Communicate findings and methodology to product and engineering
- Develop clustering and behavioral similarity approaches
- Develop survival analysis and retention models
- Document methodology assumptions and validation approaches
- Establish statistical significance and uncertainty quantification
- Own end to end analytical design for proactive insights
- Review production results against statistical expectations
Perks/Benefits
- N/A
Skills/Tech-stack
ARIMA | Causal Inference | Clustering | Cox Proportional Hazards | Difference-in-differences | Exponential Smoothing | Feature Engineering | Instrumental Variables | Kaplan-Meier | Pandas | Propensity Score Matching | Propensity score | Python | Regression discontinuity | SQL | Scikit-learn | Score Matching | Series forecasting | StatsModels | Survival analysis | Time Series | Time Series Forecasting
Education
Roles
Regions
Countries
States
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