ED, Advanced Analytics and Modeling

• Define and evolve the integrated

, capability roadmap, maturity agenda, and investment priorities aligned with business and portfolio needs.

• Lead and prioritize the portfolio across Precision Health, Key Drivers and Action Planning Analytics, Integrated Promotion Mix Modeling and Resource Optimization, and AI and Unstructured Intelligence .
• Establish transparent demand intake, prioritization, service levels, and portfolio governance across brands, launches, therapeutic areas, functions, and enterprise initiatives.
• Allocate US and Hyderabad resources to the highest-value business priorities, balancing near-term decision support with long-term capability development and reusable solutions.
• Hold capability leaders accountable for differentiated roadmaps, methodological excellence, talent development, reusable assets, and measurable business impact.
• Establish standards for analytical rigor, validation, interpretability, reproducibility, documentation, privacy, compliance, peer review, and responsible AI.
• Incubate

capabilities, including NLP, GenAI, text analytics, unstructured signal detection, evidence synthesis, and knowledge acceleration.

• Partner with senior Commercial, Medical, Market Access, Patient Services, Strategy, Finance, and Forecasting leaders to translate strategic priorities into actionable analytical agendas and recommendations.
• Partner with SPT (Strategy, Platforms, and Transformation) to define decision rights and ensure effective transition of scalable models and use cases into governed products, integrated solutions, ModelOps, and enterprise deployment.
• Lead the global US-Hyderabad operating model and develop the Associate Director engagement bench through coaching, strategic deployment, capability alignment, succession planning, and end-to-end accountability for decision impact.

• Minimum 12+ years of progressive leadership experience in advanced analytics, data science, decision science, commercial analytics, healthcare analytics, or a related quant field.
• Bachelor's degree in related field is required; Master of Science and/or MBA preferred
• Proven success defining and executing advanced analytics strategies, capability roadmaps, maturity agendas, and investment priorities across multiple analytical domains.
• Experience leading senior capability owners, flexible expert teams, complex portfolios, and globally distributed analytics organizations.
• Demonstrated expertise applying advanced analytics to high-impact commercial, patient, healthcare, launch, or enterprise decisions.
• Broad technical fluency across predictive modeling, patient analytics, driver analysis, causal inference, experimentation, promotion-mix modeling, ROI analysis, response curves, optimization, NLP, GenAI, and unstructured analytics.
• Experience establishing portfolio prioritization, capacity allocation, analytical quality governance, and reusable capability models.
• Strong judgment regarding methodological fit, evidence quality, validation, interpretability, uncertainty, model risk, privacy, and responsible AI.
• Proven ability to frame executive-level decisions, translate complex analytics into strategic choices, influence senior business and technology leaders, resolve conflicts, and manage portfolio trade-offs.
• Experience leading operating-model transformation, global delivery, organizational change, talent development, succession planning, and the division of analytical and technical ownership across models, products, platforms, ModelOps, and lifecycle management.

Desirable Requirements:

• Experience within pharmaceutical, biotechnology, life sciences, healthcare, or other highly regulated industries, with demonstrated expertise across product launches, customer and patient analytics, promotional effectiveness, market access, and healthcare delivery decision-making.
• Proven experience building and scaling AI-enabled analytics capabilities, including NLP, GenAI, unstructured-data analytics, experimentation, simulation, and optimization, while establishing integrated operating models across global capability centers and partnering effectively with data, analytics, product, platform, and technology organizations.

Novartis Compensation Summary:

The salary for this position is expected to range between $225,400.00 and $418,600.00 per year.

The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.

Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards. US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.

EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status.

Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to us.reasonableaccommodations@novartis.com or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.

Salary Range

$225,400.00 - $418,600.00

Skills Desired

Agile Methodology, Artificial Intelligence (AI), Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategies, Data Visualization, Deep Learning, Generative AI, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Mentorship, Neuro-Linguistic Programming (NLP), Organizational Awareness, Stakeholder Engagement, Statistical Analysis, Time Series Analysis, Vision Planning