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Tier-1 employer and metro location increase applicant density, but seniority and specialized skills limit competition.
Role favors biotech/pharma and regulated forecasting experience, reducing cross-industry transferability.
Explicit 15+ years, 7+ years leadership, and extensive mandatory ML and regulated-experience requirements make filters strict.
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Lead and develop the Forecasting data science team responsible for enterprise forecasting, uncertainty-aware decision support, scenario planning, and AI-enabled automation across multiple business functions.
Define and execute the data science strategy and roadmap for forecasting and decision-support solutions, ensuring measurable business impact, adoption, governance, and continuous improvement.
Partner with cross-functional senior stakeholders to identify high-impact forecasting opportunities, translate ambiguous problems into prioritized initiatives, and oversee prototype-to-production delivery of AI/ML products.
15+ years professional experience in data science, machine learning, forecasting, AI, analytics, or decision-support solutions with measurable business value.
7+ years experience managing and leading data science or AI teams.
Strong expertise with forecasting, predictive modeling, uncertainty quantification, scenario analysis, and associated statistical methods.
Proficiency in Python, R, SQL and familiarity with modern ML frameworks and MLOps; plus experience with production deployment and AI governance in regulated environments.
Senior leader experienced in setting data science strategy and managing large, cross-functional portfolios in ambiguous, high-impact enterprise environments.
Deep domain experience in forecasting, decision intelligence, or operational analytics particularly in regulated or complex sectors such as biotech, pharma, healthcare, or supply chain.
Proven track record delivering production-grade AI/ML forecasting and decision-support products with strong stakeholder influence and governance expertise.