Data Scientist
Tasks
- Apply explainability and fairness techniques
- Build scalable machine learning pipelines
- Collaborate with engineers and product teams to integrate models
- Design end-to-end machine learning solutions
- Develop feature engineering pipelines
- Develop feature stores and reusable data assets
- Monitor model drift performance degradation and anomalies
- Operationalize models with CI CD and MLOps
- Run A/B tests and causal inference experiments
- Train, validate, and deploy machine learning models
Perks/Benefits
- Employee resource groups
- Generous parental leave
- Hybrid work flexibility
- Mental health and well being initiatives
- Paid birthday leave
- Paid study leave
- Paid volunteering leave
- Sponsored social clubs team events and celebrations
- Training and personal growth support
Skills/Tech-stack
A/B | A/B Testing | AWS Bedrock | AWS SageMaker | B testing | CI/CD | Causal Discovery | Causal Inference | Databricks | Decision Trees | Delta Lake | Ensemble learning | Feature Engineering | Feature Store | Kubeflow | Linear Regression | Logistic Regression | MLOps | MLflow | Machine Learning | Model Monitoring | Model versioning | PySpark | PySpark MLlib | PyTorch | RAG | Retrieval-Augmented Generation | SQL | Scikit-learn | Statistical modeling | TensorFlow | Uplift Modeling
Education
N/A
Roles
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