Associate Director, Market Access & Patient Services Analytics

Key Responsibilities

• Scope and lead deep-dive analytics projects that surface strategic opportunities across the access and patient services landscape — e.g., quantifying how payer behaviors, utilization management, contracting decisions, and channel mix shifts impact covered demand and brand performance
• Drive payer and access decision analytics, including reimbursement scenario modeling, access impact quantification of coverage decisions, and analytical inputs that sharpen contracting and pull-through strategy
• Synthesize findings into compelling, executive-ready narratives that influence resource allocation, program design, and access strategy at the leadership level, with results that inform decisions across multiple functions and may materially impact broader commercial strategy
• Anticipate future analytical needs (e.g., evolving payer and policy landscapes, competitive entrants, new product launches) and contribute to building the frameworks and capabilities to address them
• Build, validate, and deploy predictive and statistical models that anticipate patient drop-off risk, time-to-therapy bottlenecks, payer policy impacts, and demand shifts, enabling proactive rather than reactive intervention
• Apply established analytical principles and introduce new methods where they add value, leveraging machine learning, segmentation, and experimental design to large proprietary datasets (SP, hub, claims, formulary) to optimize program effectiveness and forecast access trends
• Design and analyze operational experiments and pilots (e.g., program design changes, intervention targeting) to establish what actually moves outcomes, building a culture of test-and-learn
• Conduct patient journey analytics that go beyond KPI tracking — e.g., understanding free trial, QuickStart, and bridge program utilization by payer and coverage status to inform affordability strategy and gross-to-net implications
• Identify and resolve operational bottlenecks across the patient journey using data to optimize demand/capacity levels and vendor/partner performance (referral-to-start, prior authorization cycles, hub hand-offs, and specialty pharmacy pull-through)
• Analyze pull-through performance across payer accounts, specialty pharmacies, and prescriber segments, linking formulary wins to script volume, prior authorization approval rates, and SP dispense data to identify where access is theoretically available but not being realized in practice, and recommending targeted interventions to close the gap
• Engineer and automate complex data crosswalks (e.g., contracts-to-dispense mapping, SP/SD customer alignment, GPO/IDN/provider rollups) that turn fragmented data into clean, decision-grade assets and eliminate recurring manual effort
• Establish scalable, self-service reporting and dashboards ecosystems so analytical capacity is freed for higher-order strategic work
• Continuously raise the bar on data quality, payer spine standardization, documentation, and analytical reproducibility across patient services and access data assets
• Serve as a recognized subject matter expert on patient services and access analytics, modeling strong standards for analytical rigor, methodology, and design within the Commercial Analytics & Operations team, and providing thought leadership through reusable methods and frameworks adopted by others
• Partner with Market Access, Patient Services, Trade & Distribution, Forecasting, and brand-aligned Commercial Analytics leads to integrate access and patient services insight into holistic brand strategy and performance views
• Inform the data and vendor strategy for access and patient services analytics, contributing to evaluation and integration of sources such as SP data feeds, hub data, adjudicated claims, formulary databases, and patient registry data against future analytical needs, not just current reporting
• Prioritize and deliver high-impact ad hoc analyses for Market Access, Patient Services, brand, and leadership stakeholders, tailoring outputs (Excel, PPT, written narrative) to the decision at hand

Requirements

• A typical candidate will have at least 12+ years of related professional experience (8+ years with an advanced degree); advanced degree in a quantitative discipline preferred
• 5+ years of hands-on experience delivering advanced analytics within the pharmaceutical/biotech industry – statistical modeling, machine learning, or experimentation – with demonstrated expertise in patient services, hub, and/or specialty pharmacy data environments
• Track record of analytics projects that influenced strategic or operational decisions, not just informed reporting; experience supporting analytics for one or more product launches required, multiple launches preferred
• Comfort operating with autonomy and ambiguity, structuring open-ended problems, devising solutions from limited information, and managing competing priorities in a lean, fast-moving organization
• Recognize internally and/or externally as a subject matter expert in access and/or patient services analytics, with a track record of shaping analytical approaches and business decisions
• Strategic & Communication Skills: Demonstrate ability to operate as a thought partner to senior stakeholders – critically interrogating data, challenging assumptions, and shaping the question as well as the answer
• Excellent interpersonal, oral, and written communication skills, with the ability to distill complex modeling and access analytics into clear, actionable recommendations and compelling narratives that drive executive decision making – frame insights as coherent story with a clear ‘so-what’ and recommended path forward
• Exceptional collaboration skills, with the ability to work effectively as an individual contributor and driver of alignment across Market Access, Trade & Distribution, Patient Services, brand-aligned Commercial Analytics leads, and IT
• Technical And Domain Expertise: Strong applied experience with machine learning, statistical analysis, predictive modeling, and analytics design for operational experimentation
• Proficiency with SQL required; proficiency with at least one programming language a plus (Python or R strongly preferred); experience with distributed/big-data tooling (e.g., Spark) a plus
• Demonstrated expertise with specialty pharmacy datasets, including patient status/sub-status, dispense, hub performance, and patient affordability programs (co-pay, free drug, QuickStart/bridge)
• Strong working knowledge of market access data types: formulary/coverage databases, adjudicated claims, prior authorization and appeals data, and payer mix analysis
• Baseline understanding of access barriers, payer behaviors, contracting dynamics, patient support flows, and channel mix changes impacting covered demand
• Familiarity with building and maintaining payer spines and standardizing payer information across datasets; experience automating data crosswalks and customer mapping a plus
• Experience with real-world datasets such as medical claims, pharmacy claims, labs, and EHR data; pharmacy and medical benefit experience preferred
• Experience with Power BI, Tableau, or other data visualization tools, including dashboard development
• Familiarity with indication expansion dynamics preferred, particularly transitions from rare to broader patient populations; rare disease data management/analysis experience a plus
• Exposure to HEOR datasets, real-world evidence methodologies, or gross-to-net analytics preferred
• Familiarity with Courier Health, Claritas Rx, or other patient-oriented CRM/field force platforms as data sources preferred