Director, Commercial Data Science & AI/ML — Vaccines

GSK•Philadelphia, PA

4d•Hybrid

About The Position

You will lead high-impact data science and AI/ML initiatives that drive commercial strategy across our Vaccines portfolio, spanning adult immunization programs, pediatric vaccine schedules, and public health partnerships. Working closely with commercial, market access, medical, and public health teams, you will transform complex vaccines data into actionable insights that optimize immunization coverage, shape go-to-market strategies and improve patient access. We value strategic thinkers who understand the unique intersection of public health dynamics and commercial imperatives in the vaccines space — and who inspire and grow the teams around them. This role offers significant visibility, leadership influence, and the opportunity to align with GSK's mission of uniting science, technology, and talent to get ahead of disease together. Responsibilities: This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:

Requirements

Advanced degree (Master's or PhD) in Data Science, Computer Science, Statistics, Applied Mathematics, Epidemiology, or a related quantitative field.
10+ years of hands-on experience in applied data science, machine learning, or statistical modeling, with at least 3 years in a pharmaceutical or biotech commercial setting, preferably with vaccines or immunology exposure.
Demonstrated experience working with vaccines or commercial pharma data assets, including IQVIA (e.g., LAAD, DDD, Xponent), Optum (e.g., Clinformatics, claims data), Symphony Health, or immunization information systems (IIS/registries), with the ability to assess data quality, coverage, and appropriate use cases for each.
Strong programming skills in Python or R, experience with relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost), and demonstrated ability to leverage AI-powered development tools (e.g., GitHub Copilot, Cursor, or LLM-based coding agents) to accelerate and enhance programming workflows.
Experience deploying models and building end-to-end ML pipelines using cloud platforms (AWS, Azure, or GCP) or containerized services.
Proven ability to lead complex, cross-functional commercial analytics projects and influence senior stakeholders in a matrixed organization spanning both commercial and public health priorities.
Excellent written and verbal communication skills with the ability to translate complex analytical outputs into clear commercial and public health recommendations for vaccines business leaders.

Nice To Haves

PhD in a quantitative, life science, epidemiology, health economics, or immunology-related discipline.
Deep therapeutic area expertise in vaccines, with working knowledge of both adult immunization programs (e.g., RSV, flu, pneumococcal, shingles) and pediatric vaccine schedules (e.g., combination vaccines, ACIP-recommended schedules).
Experience modeling vaccination coverage dynamics, including geographic and demographic under-vaccination analysis, seasonal demand fluctuation, and the impact of public health campaigns or ACIP recommendation changes on commercial performance.
Familiarity with NLP or large language models applied to vaccines commercial use cases, such as HCP sentiment mining, public health policy monitoring, or patient and provider communication optimization.
Experience with MLOps practices including feature stores, model governance frameworks, and automated monitoring in a regulated pharmaceutical environment.
Track record of building and developing high-performing data science teams in a global, commercial pharma environment.
Knowledge of vaccines-specific compliance frameworks governing commercial data use, including HIPAA, PhRMA Code, FDA promotional guidelines, and CDC/public health data use agreements.
Familiarity with government vaccine programs such as Vaccines for Children (VFC), 317 program, and federal contract dynamics and their analytical implications for commercial strategy.

Responsibilities

Lead the design, development, and delivery of advanced predictive models and AI/ML solutions that support commercial decisions across the Vaccines portfolio, including launch readiness, immunization coverage gap identification, promotional response modeling, and vaccination program performance analytics.
Partner with Commercial, Market Access, Public Health, Medical Affairs, and Marketing teams to translate business and public health questions into analytical plans with measurable impact on vaccination rates, revenue, and patient outcomes.
Build, validate, and operationalize end-to-end machine learning workflows — from data ingestion and feature engineering through model deployment, monitoring, and performance tracking — leveraging vaccines commercial data assets such as claims, immunization registries (IIS), EMR, specialty pharmacy, and public health surveillance data.
Develop and apply AI/ML methods to vaccines-specific commercial challenges, including demand forecasting and inventory optimization, geographic coverage gap analysis, HCP and pharmacist targeting and segmentation, pediatric schedule adherence modeling, and payer and public health program dynamics.
Apply data science to adult immunization priorities, including identifying under-vaccinated adult populations, optimizing seasonal and non-seasonal vaccine campaigns, modeling public health partnership impact, and supporting reimbursement strategy for recommended adult vaccines.
Lead market access analytics specific to vaccines, including payer mix modeling, formulary and ACIP recommendation impact analysis, government contract and VFC program analytics, and net price optimization across commercial and public health channels.
Lead and mentor a team of data scientists and analysts, setting technical standards, fostering reproducible and responsible AI practices, and building a high-performing, collaborative team culture.
Communicate complex analytical findings clearly and persuasively to senior commercial and public health leaders, enabling evidence-based decisions on strategy, investment, and resource allocation in the vaccines business unit.
Champion the adoption of modern AI/ML tools, GenAI applications, and scalable data infrastructure to continuously elevate the commercial analytics capability across the vaccines organization.
Collaborate with IT, Data Engineering, and external vendors to ensure data quality, governance, and compliance with relevant privacy and regulatory standards (e.g., HIPAA, GDPR, FDA promotional guidelines).