Senior Market Access Specialist, Data and Analytics (Remote)

Nestle Operational Services Worldwide SA•Bridgewater Township, NJ

4d•$125,000 - $160,000•Remote

About The Position

The Senior Market Access Specialist - Data and Analytics, plays a critical role in enabling data-driven and AI-enabled decision-making across the Market Access organization and the Sales Field. This position is responsible for building end-to-end data and AI solutions — from raw data ingestion through analytics, visualization, predictive modeling, and storytelling — that make the organization smarter, more actionable, and better equipped to compete in the pharmaceutical industry. The role leverages SQL, Power BI, AI/Generative AI (e.g., Microsoft Copilot, Azure OpenAI), and other modern analytics tools to transform fragmented pharma datasets (payer claims, wholesaler EDI, copay, PAP, and specialty pharmacy journey data) into clear, decision-ready insights. The Sr. Specialist partners closely with Market Access leadership, Trade, Payer Strategy, Patient Services, Sales Operations, Finance, IT, and external partners (specialty pharmacies, wholesalers, copay/PAP vendors) to translate business needs into technical and AI-powered solutions that drive revenue growth, protect gross-to-net, and improve the patient experience.

Requirements

BS / BA required (Master's preferred) in Data Science, Computer Science, Information Technology, Statistics, Applied Math, Economics, Information Systems, Business Administration, or related field. Equivalent working experience also acceptable.
5+ years of progressive experience in data analytics, business intelligence, or data engineering — preferably in pharmaceutical, life sciences, or healthcare environments
Hands-on experience with pharma data assets including payer claims, wholesaler EDI 852/867, specialty pharmacy data feeds, copay/PAP transactional data, and 867/852-equivalent sales-out data
Demonstrated experience designing and delivering production-grade Power BI dashboards and SQL-based data models
Working experience applying AI, machine learning, and/or Generative AI tools (e.g., Microsoft Copilot, Azure OpenAI, ChatGPT Enterprise, Python ML libraries) to deliver business solutions
Strong understanding of Market Access concepts including gross-to-net, payer coverage, formulary dynamics, prior authorization, prescription abandonment, and specialty distribution

Responsibilities

Design, build, and maintain SQL-based data models and Power BI dashboards that integrate payer claims, EDI 852/867, copay, PAP, and specialty pharmacy data
Develop automated, production-grade reporting solutions that replace manual spreadsheets and accelerate decision cycles
Build self-service analytics products tailored to Market Access leaders, payer account managers, trade managers, and field sales teams
Apply best-in-class data engineering practices (data validation, version control, documentation) to ensure scalability and reliability
Embed AI and Generative AI capabilities (e.g., Microsoft Copilot, Azure OpenAI, natural language query) into dashboards and solutions to enable conversational analytics and faster self-service insight discovery
Prototype and operationalize machine learning models (e.g., abandonment risk, persistence prediction, gross-to-net forecasting) in partnership with IT and data science partners
Analyze payer patient claims data to surface coverage trends, prior auth/step edit impact, prescription abandonment, and net price dynamics
Mine wholesaler EDI 852 (inventory) and EDI 867 (sales-out) data to identify channel trends, demand signals, and inventory health across distribution partners
Translate patient services data (copay utilization, max-out rates, PAP enrollment velocity, specialty pharmacy fill rates and time-to-fill) into actionable insights for patient experience improvement
Partner with Payer Strategy, Trade, Patient Services, and Field Sales to define KPIs and answer the "so what" behind the data
Leverage AI-driven anomaly detection and pattern recognition to proactively flag coverage shifts, channel disruptions, and patient access risks before they impact performance
Build prescription journey analytics in partnership with specialty pharmacy partners to track each patient touchpoint — referral, BV/PA, copay adjudication, first fill, refill, persistence, and discontinuation
Identify drop-off points, friction, and intervention opportunities across the patient journey
Provide insights that inform copay program design, PAP eligibility expansion, and EMR/e-coupon optimization
Apply predictive AI/ML models to identify patients at risk of abandonment or non-persistence and recommend targeted, data-informed interventions
Develop analytics that monitor gross-to-net drivers (rebates, copay spend, PAP cost, returns, chargebacks) and surface variance early
Support top-line growth analytics through demand forecasting, contract performance tracking, and pull-through measurement
Partner with Finance and Government Pricing to ensure analytical consistency across reporting outputs
Use AI-powered forecasting and scenario modeling to stress-test gross-to-net assumptions and accelerate financial planning cycles
Establish standardized business rules, definitions, and reporting logic across Market Access datasets
Partner with IT, Master Data, and external data vendors to resolve quality issues and improve data freshness/completeness
Maintain trusted, audit-ready datasets used in executive-level reporting
Champion responsible AI principles — including data privacy, model transparency, and compliance with HIPAA and pharma regulatory requirements — in all AI-enabled solutions