Data Scientist

Key Responsibilities

• Collaborate with stakeholders across business units to identify data-driven opportunities and develop innovative business solutions
• Analyze complex datasets using advanced statistical methods to uncover hidden patterns and generate actionable insights
• Design and develop customized machine learning and AI algorithms tailored to specific customer requirements
• Create scalable, reusable AI/ML/statistical models that can be deployed across multiple business units with minimal customization
• Translate analytical findings into clear, actionable recommendations for business and product improvement
• Partner with product and engineering teams throughout the project lifecycle to ensure data requirements are well-defined and properly captured
• Lead product and project initiatives independently while providing technical guidance and mentorship to team members
• Develop and maintain interactive dashboards using tools such as Power BI to communicate algorithm results and insights to stakeholders
• Communicate complex analytical concepts effectively to audiences at all organizational levels through clear, data-driven storytelling

Technical Responsibilities

• Perform comprehensive data exploration, preprocessing, data transformation, validation, reconciliation, feature engineering, and quality assurance using Python
• Apply analytical and advanced machine learning algorithms including regression, classification, clustering, support vector machines, decision trees, random forests, and neural networks
• Implement specialized analytics techniques such as design of experiments, forecasting, segmentation, and uncertainty analysis
• Develop and deploy APIs and web applications using Flask or Django frameworks
• Deploy models to cloud platforms such as Azure or AWS with containerization using Docker and CI/CD pipelines
• Develop efficient and maintainable Python solutions for processing, transforming, validating, and reconciling large datasets, including handling millions of records
• Implement deterministic business logic, configurable validation rules, error handling, and data-quality checks for complex real-world datasets

Qualifications

B.E / B.Tech or equivalent technical qualification

Strong programming fundamentals in Python and experience working with structured and large-scale datasets.

Additional Information

3 to 6 years

B.E

3 to 6 years