Senior Data Scientist

Title: Senior Data Scientist

Years of Experience

*Location:

The Senior Data Scientist will lead the development and implementation of advanced analytics and AI/ML models to solve complex business problems. This role requires deep statistical expertise, hands-on model building experience, and the ability to translate raw data into strategic insights. The candidate will collaborate with business stakeholders, data engineers, and AI engineers to deploy production-grade models that drive innovation and value.

Key responsibilities

• Lead end-to-end model lifecycle: data exploration, feature engineering, model training, validation, deployment, and monitoring
• Develop predictive models, recommendation systems, anomaly detection, NLP models, and generative AI applications
• Conduct statistical analysis and hypothesis testing for business experimentation
• Optimize model performance using hyperparameter tuning, ensemble methods, and explainable AI (XAI)
• Collaborate with data engineering teams to improve data pipelines and quality
• Document methodologies, build reusable ML components, and publish technical artifacts
• Mentor junior data scientists and contribute to CoE-wide model governance

Technical Skills

• ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost
• Statistical tools: Python (NumPy, Pandas, SciPy), R, SAS
• NLP & LLMs: Hugging Face Transformers, GPT APIs, BERT, LangChain
• Model deployment: MLflow, Docker, Azure ML, AWS Sagemaker
• Data visualization: Power BI, Tableau, Plotly, Seaborn
• SQL and NoSQL (CosmosDB, MongoDB)
• Git, CI/CD tools, and model monitoring platforms

Qualification

• Masters in Data Science, Statistics, Mathematics, or Computer Science
• Microsoft Certified: Azure Data Scientist Associate or equivalent
• Proven success in delivering production-ready ML models with measurable business impact
• Publications or patents in AI/ML will be considered a strong advantage.