Serve as a senior trusted advisor to CIO, CTO, CDO, CRO, business, product, and technology stakeholders.
Lead Data & AI discovery and translate ambiguous business problems into measurable, production-ready solutions.
Design end-to-end architectures spanning data platforms, analytics, machine learning, GenAI, applications, APIs, governance, and integrations.
Lead and challenge advanced forecasting and predictive-modeling approaches, including regression, sparse and zero-inflated data, feature design, model selection, tuning, and validation.
Define appropriate business and model success measures, including R², WAPE, MAPE, statistical significance, and business-impact KPIs.
Ensure point-in-time correctness, prevent data leakage, and maintain rigorous model-development and validation practices.
Provide hands-on technical leadership using Python, SQL, Snowflake, notebooks, Git, and modern Data/AI platforms.
Shape AI use cases across forecasting, sponsorship sales, lead scoring, next-best-action, revenue intelligence, personalization, subscription growth, and commercial optimization.
Evaluate when classical analytics/ML, GenAI, or agentic AI is the appropriate solution.
Lead architecture and solution-design workshops and present recommendations to senior and executive audiences.
Support proposals, SOWs, RFI/RFP responses, estimates, staffing models, and technical solution shaping.
Lead and mentor multidisciplinary teams across Data Science, Data Engineering, AI Engineering, Software Engineering, and Architecture.
Actively participate in client stand-ups, backlog refinement, executive readouts, and strategic planning.
Teach and transfer knowledge to client teams; documentation, reproducibility, and handover are expected parts of delivery.
Challenge client requests when the proposed approach does not solve the underlying business problem.
Provides next-generation technology services specializing in digital transformation, offering tailor-made solutions that integrate innovative technologies and deep industry expertise.