Data Scientist
Tasks
- Analyze experimentation results
- Build analytics data products
- Build churn prediction models
- Communicate findings to non-technical audiences
- Deploy churn models
- Design A/B tests
- Design revenue attribution frameworks
- Develop propensity models
- Feature engineer training datasets
- Generate next-best-action recommendations
- Iterate on churn models
- Move models from notebook to production
- Retrain models
- Track marketing and sales impact
- Train, deploy, and monitor models
- Translate business questions into analytical problems
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS | B testing | BigQuery | Causal Inference | DBT | Data Pipelines | ECS | Experimentation | Feature Engineering | GenAI | LLM | Lambda | Machine Learning | Model Monitoring | Pandas | Python | SQL | SageMaker | Scikit-learn | Snowflake | Statistics | StatsModels
Education
N/A
Roles
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