Principal Data Scientist
USD 184K-255K (estimate) Senior-level Full Time
Tasks
- Automate production workflows with orchestration tools
- Build and maintain scalable data pipelines lakehouse warehouse feature stores
- Define problem success criteria and technical approach
- Deploy and manage model lifecycle packaging deployment serving versioning rollback
- Deploy predictive models for churn risk engagement propensity success likelihood
- Design next best action logic and productionize
- Drive production reliability cost performance optimization
- Establish feedback loops for continuous model improvement
- Implement CI/CD pipelines and infrastructure as code
- Implement ELT ETL workflows and feature pipelines for analytics and model serving
- Lead A B testing programs for retention engagement satisfaction
- Lead AI and machine learning initiatives end to end
- Mentor data scientists and engineers through code reviews and knowledge sharing
- Promote data lineage traceability explainability best practices
- Set up monitoring observability data quality checks model and data drift detection alerting retraining triggers
- Translate technical findings into executive narratives
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Airflow | B testing | CI/CD | DBT | Dagster | Data Drift | Data Drift Detection | Data Governance | Data Lineage | Data Modeling | Data Pipelines | Data Science | Databricks | Docker | Drift Detection | ELT | ETL | Experimentation | Explainability | Feature Store | Infrastructure as Code | Infrastructure automation | Kubernetes | MLOps | MLflow | Machine Learning | Model Deployment | Model Drift | Model Drift Detection | Model Monitoring | Observability | Predictive Modeling | Python | SQL | Terraform | “as-code”
Education
N/A
Roles
Data Scientist | Principal | Principal Data Scientist | Scientist
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