Role
As the Data Science (Agentic AI) Manager, you will lead end-to-end data science initiatives (e.g., machine learning, document AI, GenAI) to turn data into actionable insights that improve the speed and quality of business decisions. You will translate business objectives into scoped projects with clear success metrics, and own delivery from prototype through production launch and adoption. You will partner closely with big data, software engineering, and advanced analytics teams to design solution architectures, data pipelines, and model integration into operational workflows. You will manage timelines, budgets, and risks; ensure rigorous validation and testing; establish disciplined MLOps for reliability; and contribute to the research and development of cutting-edge methods tailored to specific business requirements and products.
Requirements
- Education: Possesses bachelor’s degree in Data Science, Applied Mathematics, Statistics, Computer Science, Electrical/Computer Engineering, or Business Analytics; Master’s/PhD preferred.
- Experience: Minimum 5+ years in leading end-to-end data science initiatives/projects with project management accountability in data science/ML/DL/OR.
- Domain: Proven delivery of production analytics solutions in finance, supply chain, engineering, and/or manufacturing, with measurable KPI/ROI outcomes.
- Advanced Analytics: Deep understanding and experience in agentic AI/GenAI, LLM, machine learning, API/system integration.
- Project management: Agile/Scrum, backlog management, milestones, RAID logs, risk/issue management, dependency handling, and cross-functional coordination with IT/application teams.
- Leadership: Mentoring and developing teams, establishing technical standards, code reviews, hiring support, vendor/tool benchmarking, and leading build-versus-buy decisions.