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.