Summary:
The Sr. Data Scientist will be responsible for developing, evaluating, and deploying advanced machine learning and statistical models to solve complex business problems. This role involves end-to-end ownership of data science solutions?from problem framing and feature engineering to model deployment and performance monitoring, particularly within Retail Banking and Consumer Finance domains.
The ideal candidate will bring deep expertise in machine learning, GenAI/LLM technologies, statistical modeling, and hands-on experience building compliant, explainable, and production-ready AI solutions using AWS cloud services including SageMaker, Bedrock, and Redshift.
Required Experience & Skills
- 8?12+ years of experience in data science, machine learning, or applied AI roles.
- Deep proficiency in Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost), and statistical modeling techniques.
- Strong hands-on experience with AWS AI/ML services, including SageMaker, Bedrock, S3, Redshift, and Lambda.
- Strong domain knowledge in Retail Banking and Consumer Finance, including lending, credit risk, fraud, payments, and customer analytics.
- Experience with GenAI/LLM technologies, vector databases, RAG frameworks, and prompt engineering.
- Proficiency in MLOps practices include model versioning, monitoring, retraining pipelines, and CI/CD integration.
- Strong understanding of model governance, explainability (SHAP, LIME), and compliance requirements in regulated industries.
- Excellent analytical, problem-solving, and communication skills with the ability to present complex findings to business leadership.