Data Scientist
About the Role
Key Responsibilities:Collaborate with stakeholders across business units to identify data-driven opportunities and develop innovative business solutionsAnalyze complex datasets using advanced statistical methods to uncover hidden patterns and generate actionable insightsDesign and develop customized machine learning and AI algorithms tailored to specific customer requirementsCreate scalable, reusable AI/ML/statistical models that can be deployed across multiple business units with minimal customizationTranslate analytical findings into clear, actionable recommendations for business and product improvementPartner with product and engineering teams throughout the project lifecycle to ensure data requirements are well-defined and properly capturedLead product and project initiatives independently while providing technical guidance and mentorship to team membersDevelop and maintain interactive dashboards using tools such as Power BI to communicate algorithm results and insights to stakeholdersCommunicate complex analytical concepts effectively to audiences at all organizational levels through clear, data-driven storytellingTechnical Responsibilities:Perform comprehensive data exploration, preprocessing, data transformation, validation, reconciliation, feature engineering, and quality assurance using PythonApply analytical and advanced machine learning algorithms including regression, classification, clustering, support vector machines, decision trees, random forests, and neural networksImplement specialized analytics techniques such as design of experiments, forecasting, segmentation, and uncertainty analysisDevelop and deploy APIs and web applications using Flask or Django frameworksDeploy models to cloud platforms such as Azure or AWS with containerization using Docker and CI/CD pipelinesDevelop efficient and maintainable Python solutions for processing, transforming, validating, and reconciling large datasets, including handling millions of recordsImplement deterministic business logic, configurable validation rules, error handling, and data-quality checks for complex real-world datasetsQualificationsB.E / B.Tech or equivalent technical qualificationStrong programming fundamentals in Python and experience working with structured and large-scale datasets.Additional Information3 to 6 yearsB.E3 to 6 years