Data Scientist
Tasks
- Apply mixed effects hierarchical models
- Architect data pipelines for audience measurement
- Calibrate linear TV and digital tracking metrics
- Deploy gradient boosted regression trees models
- Design control and test groups for experiments
- Estimate unique audience reach with maximum entropy
- Implement Bayesian statistical models
- Manage data in cloud data warehouses
- Measure causal lift with synthetic control methods
- Optimize SQL for analytics
- Perform feature engineering for media drivers
- Schedule model runs with Airflow
- Use propensity score matching to reduce selection bias
- Wrap models into production grade APIs
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS | Airflow | Bayesian Model Averaging | Bayesian Modeling | Cloud platform | Dask | Docker | Gaussian Mixture Models | Google Cloud | Google Cloud Platform | Gradient boosting | Hierarchical modeling | LightGBM | Machine Learning | Maximum Entropy | Mixed-effects | Mixed-effects models | Mixture models | Pandas | Propensity Score Matching | Propensity score | PySpark | Pymc | Python | SQL | Score Matching | Snowflake | Stan | Synthetic control | XGBoost
Education
Roles
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