Sr Principal Data Scientist
Tasks
- Architect agentic AI systems
- Define modeling evaluation and experimentation standards
- Design production monitoring and model governance
- Ensure privacy aggregation and customer trust
- Lead data foundations and knowledge layer systems
- Mentor and raise bar for data science team
- Partner with product and engineering leaders on strategy roadmap
- Set technical direction for applied machine learning
- Ship high leverage machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic AI | Causal Inference | Causal ML | Contextual Bandits | Databricks | Deep learning | Difference-in-differences | Drift Detection | Experimental Methods | Feature Engineering | Foundation Model | Foundation Model Embeddings | Gradient boosting | Hypothesis Testing | LightGBM | Linear Models | Machine Learning | Model Embeddings | Model Monitoring | Multiple Comparisons | Offline Reinforcement Learning | Power analysis | Propensity Score Matching | Propensity score | PyTorch | Python | Quasi Experimental | Quasi-experimental methods | Regularized Linear Models | Reinforcement Learning | Retraining | SQL | Scikit-learn | Score Matching | Sequential testing | Snowflake | Spark | Synthetic control | Tableau | Transformer | Uplift Modeling | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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