Job Description Summary The ideal location for this role is East Hanover, NJ but a distant working arrangement may be possible in certain states. Distant workers are responsible for the cost of home office expenses and periodic travel/lodging to East Hanover, NJ, as determined necessary by hiring manager. The Insights and Decision Science (IDS) team is dedicated to enabling improved decision making at Novartis by leveraging data and advanced analytics capabilities to generate actionable insights that drive business growth. We collaborate closely with the US business, bringing insights and challenging ideas to empower smarter, data-driven decision-making. Reporting into the VP, Decision Science TA and Launch this role is crucial in enabling proactive and integrated insight-driven decision making for the brand, addressing business problems, shaping strategy and implementing decision science through IDS capabilities. The Decision Science, Product Lead is a strategic leader responsible for transforming complex data into actionable insights that drive brand success. This role is pivotal in integrating and synthesizing information from diverse sources to provide comprehensive, actionable answers that align with brand strategic imperatives. By supporting the generation and analysis of insights throughout the product lifecycle as the connector between the IDS and product team, the individual ensures continuous insight-generation and strategic alignment, fostering innovation and informed decision-making. Leading a team of high-performing IDS POD at product level, this role is instrumental in shaping the brand's strategic direction, ensuring that insights are effectively. Job Description Key Responsibilities: - Shape the strategic direction of the brand by leveraging insights to identify opportunities, address challenges, and optimize performance - Integrate and synthesize insights from across IDS functions to deliver comprehensive, actionable recommendations that address key brand objectives - Actively participate in IPST discussions and decision-making, contributing data-driven insights and challenging established thinking to refine strategies - Understand and help craft the brand narrative for IPST meetings and conversations with senior leadership - Serve as the primary point of contact and proactive strategic thought partner for the Integrated Product Strategy Team (IPST) and General Management (GM), driving brand performance narrative, and ensuring consistent communication and alignment - Collaborate with the IPST Lead to further refine analyses & sharpen insights / recommendations - Lead IDS POD at product level by working across IDS pillars to direct and synthesize information to help drive brand performance - Share key insights with the IPST, while actively pressure-testing and challenging current thinking to drive innovation and informed decision-making - Support the generation and analysis of insights throughout the entire product lifecycle, ensuring continuous improvement and alignment with brand goals - Synthesize large volumes of analytics provided by GM, ensuring that insights are translated into actionable strategies for the brand - Pressure-test insights and analyses to ensure robust, high-quality recommendations that drive brand success - Integrate performance analytics (e.g., diagnose current results with aligned KPIs and drivers, provide clarity on root cause) and predictive analytics (e.g., data-driven scenarios and simulations) to explore/address business issues in the context of the brand Essential Requirements: Novartis seeks an individual with extensive experience in the pharmaceutical or healthcare industry, with a deep understanding of product lifecycle management, market dynamics, and regulatory environments. A proven track record in brand performance management, strategic planning, or a similar role, the person should demonstrate the ability to develop strategic insights that drive brand success and align with organizational goals. The candidate should be able to manage high performing teams, fostering a collaborative and innovative work environment. Additional qualifications are as follows: - Ten plus years of experience in the pharmaceutical or healthcare industry, with a deep understanding of brand management, product lifecycle management and market dynamics - A bachelor’s degree in business administration, Life Sciences, Data Science or a related field; an MBA or advanced degree is strongly preferred - Strong background in therapeutic area strategy, product lifecycle management, and early-stage asset planning, ideally with experience in both established and launch products. - five plus years of domain expertise in these areas are highly desired: secondary data analytics, data science, primary market research, field analytics and insights, market access and patient service analytics, or other related strategic analytics and management consulting - Expertise in synthesizing complex data from diverse sources to drive actionable, business-aligned insights and inform strategic decisions across the product lifecycle - Excellent communication skills, capable of effectively collaborating with senior leadership and aligning diverse teams around strategic goals for IPST. - Proficiency in insight and hypothesis generation, behavioral science, data science, and primary and secondary research methodologies. - Strong leadership skills in a team environment which requires negotiation, persuasion, collaboration, and analytical judgment. The salary for this position is expected to range between $236,600.00 and $439,400.00 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. To learn more about the culture, rewards and benefits we offer our people click here. 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 $236,600.00 - $439,400.00 Skills Desired Agility, Brand Awareness, Cross-Functional Collaboration, Customer Engagement, Customer Experience, Customer Insights, Data Analytics, Digital Marketing, digital marketing strategy, Franchise Development, Go-To-Market Strategy, Influencing Skills, Inspirational Leadership, launch strategies, Marketing Strategy, People Management, Product Positioning, Product Roadmap, Sales, Stakeholder Engagement, Stakeholder Management, Strategic Marketing

• Translate business challenges into analytical approaches and technical solutions • Develop statistical and machine learning models supporting initiatives such as demand forecasting, staffing optimization, and operational planning • Build time series models and predictive analytics solutions to support operational and commercial decision-making • Prepare, clean, and transform raw data into structured datasets suitable for statistical modeling and analysis • Identify and incorporate new data sources and variables to improve model performance and predictive accuracy • Translate model outputs into operational insights and measurable business KPIs • Develop visualizations and reporting tools that communicate model results and insights to business stakeholders • Integrate analytical outputs into operational workflows and decision-making processes • Partner with cross-functional teams across operations, technology, and analytics to prioritize and execute data initiatives • Build relationships with internal and external data and technology partners to enhance analytics capabilities

• Designing and developing bidding and optimization strategies for CPC-based auction systems, including advanced objectives such as target ROAS • Optimizing auction mechanisms (ranking, pricing, filtering) to balance platform revenue, advertiser value, and marketplace stability • Building and maintaining offline simulation environments, including counterfactual simulations and auction replay systems, to safely evaluate algorithmic changes • Designing and implementing feedback loops and control mechanisms to ensure stable and robust system behavior under dynamic market conditions • Conducting advanced ecosystem-level analytics on large-scale datasets to identify nonlinear effects, equilibrium points, and systemic risks • Designing, executing, and analyzing complex experiments and causal inference studies, accounting for network effects and long-term system impact • Contributing to the evolution toward smart, autonomous bidding and auction optimization through data-driven initiatives and roadmap development

• Designing and developing bidding and optimization strategies for CPC-based auction systems • Optimizing auction mechanisms to balance platform revenue, advertiser value, and marketplace stability • Building and maintaining offline simulation environments to safely evaluate algorithmic changes • Conducting advanced ecosystem-level analytics on large-scale datasets • Designing, executing, and analyzing complex experiments and causal inference studies • Contributing to the evolution toward smart, autonomous bidding and auction optimization