Associate Director Portfolio AI Activation

MSD•Rahway, NJ

3d•$156,900 - $247,000•Hybrid

About The Position

The Associate Director, AI Activation & Commercial Analytics is part of the AI Activation team within Digital Human Health (DHH), supporting the Specialty, Pharma & Infectious Diseases business units. The role is for a pharmaceutical commercial analytics and data science leader who understands brand, marketing, and field questions and applies traditional data science and emerging AI to improve business decisions. The Associate Director partners with brand, marketing, Market Engagement (ME), and data and technology teams to turn data into actionable insights, develop AI use cases grounded in business needs, and drive adoption of analytics and AI solutions that deliver measurable value. The role leads advanced analytics projects, supports launch readiness, develops machine learning and statistical models using pharmaceutical commercial data, and translates analytical work into recommendations for business leaders and field teams. It also provides expertise on commercial data sources, supports targeted AI pilots and broader DHH initiatives, and ensures work meets data privacy, compliance, and governance standards. The position builds data and AI literacy across commercial teams.

Requirements

At least 5 years of experience in pharmaceutical or healthcare commercial analytics, marketing analytics, or data science, with a proven record of supporting brand and marketing teams.
Strong expertise in machine learning and statistics applied to commercial questions such as HCP targeting, segmentation, predictive modeling, and promotional impact measurement.
Deep knowledge of pharmaceutical commercial data, including claims, prescription and sales, CRM, and HCP- and patient-level data, and of the commercial model, including brand, launch, market access, and field force.
Proficiency in Python, SQL, and/or R, and in data and analytics platforms such as Databricks or Dataiku.
Hands-on experience applying AI, such as generative AI or LLM-based tools, to analytics workflows, and a strong interest in deepening AI expertise.
Ability to translate complex analyses into clear, decision-ready recommendations that influence senior leaders.
Ability to align brand, ME, and cross-functional stakeholders on priorities, drive adoption of analytics and AI solutions, and manage scope with sound judgment.
People and/or matrix leadership experience, including leading cross-functional teams, global collaborators, and external partners.
Strong project management skills; resilience and adaptability; ability to balance strategic vision with operational execution.
Master's degree or PhD in Data Science, Mathematics, Economics, Computer Science, Statistics, Decision Science, Engineering, Public Health, or a related quantitative discipline.

Responsibilities

Lead advanced analytics and data science projects addressing brand and marketing priorities, including HCP targeting, customer segmentation, tiering, and promotional response.
Drive launch readiness for new products and indications through market and patient opportunity sizing, HCP universe definition and targeting, and early launch performance tracking.
Develop and apply machine learning and statistical models, including predictive and propensity models, clustering, response modeling, forecasting, and causal inference, using pharmaceutical commercial data.
Translate analytic outputs into clear, decision-ready insights and recommendations for brand leadership, marketing, and field teams.
Partner with brand, marketing, ME, and sales planning teams to frame business questions, define success metrics, and measure the impact of commercial initiatives.
Serve as a subject-matter expert on pharmaceutical commercial data sources, including claims, prescription and sales, CRM/call activity, and HCP- and patient-level data, and advise on their strengths, limitations, and appropriate use.
Identify AI opportunities grounded in business needs and support targeted AI pilots, such as targeting support, forecast validation, and barrier analysis.
Bring business context and data expertise to DHH-wide AI initiatives, connecting brand and technical teams so solutions are usable and adopted.
Ensure analytics and AI work meets data privacy, compliance, and governance standards.
Build data and AI literacy across commercial teams.