Since our founding in 2009, REGENXBIO has pioneered what’s possible in gene therapy. Today, we are advancing a pipeline of gene therapies designed to improve the lives of patients facing serious rare and retinal diseases and preparing to bring innovative new medicines to patients.

Our work is fueled by purpose and urgency because every day matters to patients and their families. At REGENXBIO, you’ll find meaningful opportunities to grow, collaborate, and contribute to the advancement of potentially transformative gene therapies. Together, our talented team is working to make a meaningful difference for patients and their families.

What we do matters.

• Design measurement frameworks that connect market development, customer engagement, field execution, account readiness, patient progression, access, treatment, and business outcomes.
• Build advanced analyses and decision-support models to identify leading indicators and early-warning signals that enable action before risks or opportunities are evident in lagging performance measures.
• Lead analytics across market sizing, patient identification, customer segmentation and targeting, referral networks, payer access, field-force optimization, territory potential, and launch performance.
• Translate complex analytical findings into clear recommendations, implications, risks, and actions for senior executives and operating teams.
• Own patient-based, demand, launch, and long-range commercial forecasting, incorporating drivers such as epidemiology, diagnosis, patient identification and eligibility, referral, treatment-center capacity, access, time to treatment, uptake, competitive dynamics, and supply considerations.
• Build key scenarios, including base, upside/downside, label, and access scenarios
• Monitor actual performance versus assumptions
• Identify, evaluate, and manage relevant data sources, including HCP, payer, claims, prescription, account, CRM, patient services, hub, specialty pharmacy, specialty distributor, shipment, digital, financial, epidemiology, market research, and competitive intelligence data.
• Oversee data ingestion, integration, customer and account master data, and aggregation processes to deliver accurate, high-quality, analytics-ready datasets.
• Develop and maintain dashboards, reports, scorecards, and KPI-tracking tools, and support recurring business reviews using Power BI, Tableau, Excel, and other business intelligence platforms.
• Develop a practical, governed roadmap for commercial AI, machine learning, generative AI, and analytical automatio

• Bachelor’s degree in statistics, mathematics, computer science, or a related quantitative discipline; relevant advanced degree strongly preferred.
• 10+ years of progressive experience in commercial analytics, data science, forecasting, business intelligence, commercial operations, or a related function 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 required, including the ability to independently extract, join, transform, validate, and analyze complex datasets.
• Strong hands-on capability in at least one of Python, R, SAS, Alteryx, or a comparable analytical platform.
• Strong proficiency with Excel and business-intelligence or visualization tools such as Power BI or Tableau.
• Demonstrated experience building advanced analytical models, customer or account segmentations, targeting analyses, field-effectiveness analyses, and decision-support tools.
• Demonstrated experience developing and maintaining patient-based, demand, launch, or long-range forecasts.
• Experience working with healthcare-provider, payer, claims, CRM, patient-services, specialty-pharmacy, specialty-distributor, shipment, financial, market-research, or other complex commercial datasets.
• Experience defining requirements for data acquisition, data integration, data warehouses or lakehouses, data aggregation, analytics-ready datasets, data quality, metadata, lineage, and governance.
• Working knowledge of statistical modeling, predictive analytics, machine learning, AI, and analytical automation.
• Ability to translate Brand strategy into analytical questions, data requirements, models, KPIs, insights, and commercial actions.
• Willingness and ability to travel up to 25%.