Director, Advanced Analytics & Modeling Key Drivers Analytics (KDA) and CoE Lead

Novartis•East Hanover, NJ

9d•Hybrid

About The Position

Lead two critical capability areas within Advanced Analytics & Modeling (AA&M): the enterprise Key Drivers Analytics (KDA) capability and an Associate Director team that scales advanced analytics solutions across the portfolio. As KDA capability owner, apply advanced multivariate and diagnostic methods to explain drivers of performance across brands, markets, accounts, customers, and geographies, translating evidence into clear, prioritized actions. Lead deployment of analytics talent across Precision Health, Integrated Promotion Mix Modeling (IPMM), KDA, AI & Unstructured Intelligence, and quarterly priorities set by the Executive Director, AA&M, so the portfolio delivers decision-ready evidence at scale. The role is ideally based at the East Hanover, NJ site, though remote work may be possible subject to legal-entity restrictions. Relocation is not provided. Remote associates are responsible for home-office expenses and travel or lodging for periodic meetings at the East Hanover site. The role requires 15% travel; working hours and travel expectations will be defined by the hiring manager.

Requirements

Bachelor’s degree in Statistics, Economics, Econometrics, Data Science, Applied Mathematics, Operations Research, or a related quantitative field.
At least 8 years of progressive experience in advanced analytics, data science, decision science, or commercial analytics in pharmaceutical, biotechnology, healthcare, or a comparably complex industry.
Previous experience leading a team, directly or indirectly.
Executive communication, stakeholder influence, and capacity-management skills.
Demonstrated leadership of driver, segmentation, diagnostic, or performance analytics programs that informed business action.
Experience leading analytical programs from business-question framing through executive recommendation, adoption, and impact measurement.
Experience leading analytics professionals, deploying talent flexibly across priorities, and delivering through globally distributed teams.
Expertise in key-driver analysis, multivariate modeling, segmentation and archetyping, performance diagnostics, and scenario analytics.
Working fluency in adjacent methods, including predictive analytics, patient analytics, IPMM/ROI, and causal inference, sufficient to lead a flexible team.
Strong judgment regarding correlation versus causation, uncertainty, confounding, data limitations, and practical significance.
Experience with statistical programming and reproducible analytical workflows.

Nice To Haves

Advanced degree in a quantitative field.
Experience in launch, account, subnational, or access analytics.
Experience partnering with technology or platform teams to productize analytical solutions.

Responsibilities

Own the enterprise KDA capability, including its roadmap, methodologies, standards, governance, and delivery across priority business decisions.
Lead and develop a team of Associate Directors, ensuring high-quality execution, talent growth, and effective deployment against enterprise priorities.
Drive an integrated US-Hyderabad operating model, partnering with Advanced Analytics leadership to align roadmap, capabilities, capacity, and delivery.
Lead end-to-end advanced analytics engagements, including business problem framing, hypothesis development, analytical design, model validation, insight generation, and recommendations.
Define and execute multivariate driver analyses, segmentation, archetyping, diagnostic assessments, and scenario modeling to identify factors influencing business performance.
Translate analytical insights into actionable recommendations, decision frameworks, and performance improvement strategies that drive measurable business impact.
Prioritize capability investments and analytics initiatives based on strategic value, business needs, capacity, and organizational objectives.
Partner cross-functionally with Customer & Patient Intelligence, SPT, and other stakeholders to support seamless execution, scalability, and adoption of analytical solutions.
Establish standards for analytical rigor, validation, reproducibility, compliance, responsible AI, documentation, and quality assurance.
Build reusable analytical assets, methods, and best practices while enabling Hyderabad teams to independently deliver increasingly complex and scalable KDA solutions.