Senior Data Scientist
Tasks
- Apply statistical methods
- Build ML models end to end
- Build data pipelines with data engineers
- Deploy models at scale
- Develop supervised ML models
- Develop unsupervised ML models
- Ensure data protection compliance
- Ensure models are causal when applicable
- Ensure models are unbiased
- Evaluate data collection approaches
- Forecast business demand
- Implement CI/CD
- Implement version control
- Maintain ML infrastructure
- Manage vulnerabilities
- Monitor model performance
- Optimize resource allocation
- Refine models over time
Perks/Benefits
- Bank holidays
- Company wide wellbeing days
- Gym membership
- Health insurance
- Hybrid work
- Life Event day
- Life insurance
- Mental health support
- Paid time off
- Volunteer days
- Wellbeing resources
- Work from anywhere scheme
Skills/Tech-stack
AWS | Amazon SageMaker | Apache Airflow | Azure | CI/CD | Causal Inference | DBT | Data Pipelines | Git | Information security | Infrastructure as Code | Machine Learning | NumPy | Optimization | Pandas | Python | SHAP | SQL | Scikit-learn | Series forecasting | Snowflake | Statistical Analysis | Supervised Learning | Terraform | Time Series | Time Series Forecasting | Unsupervised Learning | XGBoost | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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