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.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed