Director, Commercial Data, Advanced Analytics & Forecasting

Role overview

A senior leadership opportunity to build and direct the commercial data, advanced analytics, and forecasting capability for a gene therapy pipeline targeting serious rare and retinal diseases. The role owns the bridge from brand strategy to analytics framework, develops patient-based forecasts, and converts complex datasets into decision-ready insights and KPIs for executives. It combines data science, commercial strategy, and business intelligence in a launch-focused biotech environment.

Responsibilities

- Design measurement frameworks connecting market development, customer engagement, field execution, account readiness, patient progression, access, treatment, and overall business outcomes. - Build advanced analytical models and decision-support tools that surface leading indicators and early-warning signals before risks or opportunities appear in lagging performance metrics. - Lead analytics across market sizing, patient identification, customer segmentation, referral networks, payer access, territory potential, field-force optimization, and launch performance. - Translate complex findings into clear recommendations, implications, risks, and actions for senior executives and operating teams. - Own patient-based, demand, launch, and long-range commercial forecasts, integrating epidemiology, diagnosis, eligibility, referral patterns, treatment-center capacity, access, uptake curves, competitive dynamics, and supply considerations; build base, upside/downside, label, and access scenarios. - Govern data ingestion, integration, master data management, and aggregation to produce accurate, analytics-ready datasets from HCP, payer, claims, CRM, hub, specialty pharmacy, shipment, financial, and market research sources. - Develop dashboards, scorecards, and KPI-tracking tools in Power BI, Tableau, Excel, and similar BI platforms, and support recurring business reviews. - Define a practical, governed roadmap for commercial AI, machine learning, generative AI, and analytical automation.

Requirements

- Bachelor's degree in statistics, mathematics, computer science, or a related quantitative field; advanced degree strongly preferred. - 10+ years of progressive experience in commercial analytics, forecasting, data science, business intelligence, or commercial operations within pharmaceuticals, biotechnology, or healthcare. - Direct experience supporting at least one U.S. product launch from pre-launch planning through launch or early commercialization. - Advanced hands-on SQL proficiency, including extracting, joining, transforming, validating, and analyzing complex datasets independently. - Strong hands-on capability in at least one of Python, R, SAS, Alteryx, or a comparable analytical platform. - Demonstrated experience building segmentations, targeting analyses, field-effectiveness models, patient-based or long-range forecasts, and decision-support tools. - Familiarity with healthcare datasets such as HCP, payer, claims, CRM, patient services, specialty pharmacy, distributor, shipment, financial, and market research. - Experience defining requirements for data acquisition, integration, warehouses or lakehouses, governance, metadata, lineage, and data quality. - Working knowledge of statistical modeling, predictive analytics, machine learning, AI, and analytical automation. - Ability to translate brand strategy into analytical questions, data needs, models, and commercial actions. - Willingness and ability to travel up to 25%.

Benefits and work setup

- Estimated compensation range of $196,000 to $265,000 annually, with actual offer based on experience, skills, and tenure. - Annual bonus program, education assistance, paid caregiver leave, and a retirement plan with employer match. - Stock options available at all levels, plus summer hours and a comprehensive benefits package.