Founding Senior Data Scientist/ML
Tasks
- Advocate ML tooling improvements
- Build ML models
- Decide model registry architecture
- Define ML practices
- Design evaluation frameworks
- Design feature store strategy
- Implement evaluation harnesses
- Manage model retraining pipelines
- Own model deployment and monitoring
- Perform causal inference
- Run A/B tests
- Set ML standards and best practices
- Translate business problems to modeling questions
- Validate model impact in production
Perks/Benefits
- Generous PTO
- Hybrid work environment
- Learning and development budget
- Lunch provided
- Parking Covered
- Paternity leave
- Private health insurance
Skills/Tech-stack
A/B | A/B Testing | Agents | Airflow | B testing | BI | Causal Inference | Cloud platform | Cloud services | DBT | Dagster | Document Understanding | Experiment design | Feature Store | GCP Vertex | GCP Vertex AI | Google Cloud | Google Cloud Platform | Google Cloud Services | Kubernetes | MLflow | Machine Learning | Model Registry | Model Serving | Monitoring | OCR | Observability | PostgreSQL | Power BI | Prefect | Prometheus | Python | Retrieval-Augmented Generation | SQL | SageMaker | Snowflake | Statistical modeling | TensorFlow | Terraform | Vector Databases | Vertex AI
Education
N/A
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