Senior AI Activation & Commercial Analytics Lead

MSD; Rahway (NJ); On-site; USD 157,000 - 247,000; Full time

Job summary

Merck in Rahway, NJ seeks an Associate Director for AI Activation & Commercial Analytics to lead analytics and AI initiatives. You will partner with brand, ME, and data teams to define business questions, shape AI use cases, and drive adoption of insights that affect brand strategy and launch plans.

You will design ML models, translate outputs into actionable recommendations, and ensure governance and data privacy in all efforts.

Qualifications

• 5+ years of experience in pharmaceutical or healthcare commercial analytics.
• 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."

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.

Skills

Python

SQL

R

Databricks

Dataiku

Machine learning

Statistical modeling

HCP targeting

Segmentation

Leadership

Education

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

Tools

Databricks

Dataiku

Job description

Merck in Rahway, NJ seeks an Associate Director for AI Activation & Commercial Analytics to lead analytics and AI initiatives. You will partner with brand, ME, and data teams to define business questions, shape AI use cases, and drive adoption of insights that affect brand strategy and launch plans.

You will design ML models, translate outputs into actionable recommendations, and ensure governance and data privacy in all efforts.