Product Manager - Data Analytics AI & Data Strategy

Role Overview We are seeking a strategic, high-impact Product Manager to bridge the gap between complex data science and commercial execution. In this role, you will lead clients through the full data lifecycle—from unlocking real‑world data (RWD) insights to deploying sophisticated, AI‑driven decision analytics. You will be instrumental in helping organizations find product‑market fit, optimize commercial operations, and scale through the power of Generative AI and advanced data modeling. Key Responsibilities AI Strategy & Productization: Design, build, and deliver AI‑driven solutions tailored to commercial challenges, with a heavy focus on decision analytics and predictive modeling. RWD & Commercial Insights: Leverage deep expertise in Real-World Data (RWD) to extract actionable intelligence that drives market access and evidence‑based commercial strategies. Cross‑Functional Leadership: Lead and mentor high‑performance teams (3+ members) to execute complex data growth initiatives and streamline operational workflows. Executive Stakeholder Management: Serve as the primary partner for client leadership, translating complex technical findings into clear, high‑impact strategic recommendations for C‑suite executives. Product‑Market Fit Analytics: Conduct rigorous analytical deep‑dives to evaluate product performance, optimize commercial health, and identify strategic partnerships or market expansion opportunities. Data Operations & Growth: Architect and refine data acquisition strategies and scalable operational workflows to maximize the ROI of data assets. Required Skills & Qualifications Experience: 5+ years of proven success in Data Analytics, Data Science, Product Management, or Strategy Consulting. Domain Expertise: Strong background in Life Sciences, BioTech, or Healthcare , with deep familiarity in Real‑World Evidence (RWE) or Commercial AI applications. Technical Proficiency: Expert‑level SQL and data visualization skills. Direct experience managing or applying AI/ML frameworks within a commercial or clinical context. Leadership: Demonstrated experience leading analytics projects, managing small teams, and driving cross‑functional alignment. Communication: Exceptional data storytelling skills with a track record of influencing external stakeholders and executive‑level decision‑makers. Education: Advanced degree (Master's or Ph.D.) in Data Science, Business Analytics, Engineering, or a related quantitative field. #J-18808-Ljbffr