• Hands on design, development, deployment, and maintenance of data analytics, advanced analytics, data science and AI solutions. • Lead end-to-end delivery of data science & advanced analytics engagements. • Translate complex business problems into analytics and machine learning solutions. • Perform diagnostic analytics / causal / driver analysis for complex business problems • Develop predictive, prescriptive, and optimization models for enterprise use cases. • Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences). • Creates machine learning models for tasks like customer segmentation, sales forecasting, and churn prediction. • Applies techniques in causal inference and quasi-experimental design (e.g., matching, ITS) to determine the incremental effect of programs and interventions. • Design and implement AI-enabled analytics solutions, including forecasting, customer and revenue analytics, risk and anomaly detection, in-process intelligence and optimization. • Selects appropriate modeling techniques for complex problems with large scale, multiple structured and unstructured data sets. • Performs model assessment & optimization. • Applies best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles. • Writes queries (BigQuery, SQL …) and scripts to gather, clean, and pre-process raw structured and unstructured data for data science tasks. • Write scripts to automate data cleaning and fusion processes. • Helps manage, maintain, and improve client data sources. • Works with data engineering to deploy scripts and models as reliable pipelines. • Solid understanding of data manipulation and database technologies (SQL, NoSQL). • Strong knowledge of machine learning algorithms and libraries (e.g., Scikit-Learn, TensorFlow, PyTorch). • Build reusable analytics accelerators, frameworks, and industry solutions. • Develop solutions around AI-driven BI, Agentic AI applications, AI-assisted data management, GenAI / LLM based innovative solutions etc. • Create Proof-of-Concepts, Prototypes for innovative solutions. • Work closely with client stakeholders including CFO, FP&A, operations, and IT leadership. • Mentor and lead teams of data analysts, data engineers, and data scientists. • Facilitate workshops on data strategy, analytics roadmap, and AI adoption. • Serve as a trusted advisor to clients on data-driven decision making. • Ability to establish and maintain strong working relationships with external and internal IT partners • Support sales and business development activities including proposals and solution architecture. • Present insights and recommendations to senior executives and business leaders. • Ability to manage multiple projects / clients at the same time and work in an agile fashion. • Performing change management support for stakeholders.