Data Scientist
Tasks
- Apply causal inference methods
- Build analytics and machine learning infrastructure
- Build predictive churn and risk models
- Define metrics with BI and data engineering
- Design, run, and analyze experiments
- Develop lead scoring models
- Partner with Go To Market stakeholders
- Predict expansion likelihood and LTV
- Validate and maintain machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Airflow | B testing | Causal Inference | Difference-in-differences | LTV | Looker | MLOps | MLOps model registry | Machine Learning | Matplotlib | Model Registry | Model Serving | Pandas | Plotly | Propensity scoring | Python | SQL | Scikit-learn | Seaborn | Snowflake | StatsModels | Streamlit | Synthetic control | Tableau
Education
Roles
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