Associate Director, Portfolio AI Activation

Location: North Wales

Job Description The Associate Director, AI Activation & Commercial Analytics is a member of the AI Activation team within Digital Human Health (DHH), supporting the Specialty, Pharma & Infectious Diseases business units. This role is designed for a pharmaceutical commercial analytics and data science leader who brings a deep understanding of brand, marketing, and field questions, and who can apply both traditional data science (machine learning, targeting, and segmentation) and emerging AI to drive better business decisions.

The Associate Director partners closely with brand, marketing, and Market Engagement (ME) teams, as well as data and technology partners, to turn data into actionable insights, shape AI use cases grounded in real business needs, and drive adoption of analytics and AI solutions that deliver measurable value.

Primary Job Function and

Key Responsibilities .

Lead advanced analytics and data science projects that address priority brand and marketing questions, including healthcare professional (HCP) targeting, customer segmentation, tiering, and promotional response.

Drive launch readiness for new products and indications through analytics such as market and patient opportunity sizing, HCP universe definition and targeting, and early launch performance tracking.

Develop and apply machine learning and statistical models (e.g., predictive and propensity models, clustering, response modeling, forecasting, 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 (e.g., claims, prescription and sales, CRM/call activity, HCP- and patient-level data), including their strengths, limitations, and appropriate use.

Identify AI opportunities grounded in real business needs and support targeted AI pilots (e.g., targeting support, forecast validation, barrier analysis).Bring business context and data expertise to DHH-wide AI initiatives, bridging brand and technical teams so solutions are usable and adopted.

Ensure analytics and AI work meets data privacy, compliance, and governance standards, and build data and AI literacy across commercial teams.

Required Experience & Skills.
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 (e.g., claims, prescription and sales, CRM, HCP- and patient-level data) and 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 (e.g., generative AI or LLM-based tools) to analytics workflows, with a strong interest in deepening AI expertise.

Translates complex analyses into clear, decision-ready recommendations that influence senior leaders.

Aligns brand, ME, and cross-functional stakeholders on priorities, drives adoption of analytics and AI solutions, and manages scope with sound judgment.

People and/or matrix leadership experience, including leading cross-functional teams, global collaborators, and external partners.

Strong project management skills; resilient and adaptable, balancing strategic vision with operational execution.

Qualifications Master's degree or PhD in Data Science, Mathematics, Economics, Computer Science, Statistics, Decision Science, Engineering, Public Health, or a related quantitative discipline is required.

Required Skills:

Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Machine Learning (ML), Software Development, Stakeholder Relationship Management, Waterfall Model Preferred

Skills:

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