Senior Data Scientist
Tasks
- Analyze large datasets
- Apply responsible AI principles
- Build data pipelines
- Build predictive analytics
- Communicate insights and recommendations
- Create visualizations and dashboards
- Deploy machine learning models
- Design customer segmentation models
- Develop machine learning models
- Enhance client engagement analytics
- Identify trends and patterns
- Implement feature engineering frameworks
- Implement model governance
- Implement portfolio analytics
- Maintain statistical models
- Monitor model performance
- Optimize customer journeys
- Perform risk assessment
- Predict churn
- Recommend cross sell and up sell
- Retrain models
- Validate models
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | Churn Prediction | Classification | Clustering | Credit Risk | Credit risk modeling | Cross-sell | Customer Segmentation | Databricks | Feature Store | Fraud Detection | GCP | Generative AI | Hadoop | Keras | Language Models | Large Language Models | LightGBM | MLOps | NLP | Portfolio analytics | Power BI | PySpark | PyTorch | Python | Recommendation Systems | Regression | Risk Assessment | Risk Modeling | SQL | Scikit-learn | Series forecasting | Spark | Tableau | TensorFlow | Time Series | Time Series Forecasting | Up Sell | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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