Lead, Decision Data & Intelligence Enablement

The Lead, Decision Data & Intelligence Enablement plays a critical role in enabling enterprise decision‑making at Novartis by ensuring that data is decision grade and intelligence is applied where it creates impact. The role focuses on two core responsibilities.

• Own and establish decision‑grade data products that support enterprise portfolio decisions, ensuring that data is decision grade and AI & automation capabilities are proactively identified, shaped, and scaled to enable enterprise decision‑making impact.
• Lead the identification, prioritization, and scaling of high‑impact AI, automation, and advanced analytics use cases, ensuring trusted data foundations, clear confidence signals, and guardrails for adoption.
• Work across Andromeda & Governance Enablement (AGE), Enterprise Portfolio Insights (EPI), Data, Digital & IT and Research‑Development‑Commercial (RDC) teams to ensure that data trust is visible, measurable, and embedded into system design and execution at scale.
• Actively drive the AI and automation agenda within AGE, ensuring that opportunities are identified early, barriers are removed, and adoption is scaled with measurable enterprise impact.

• Adoption of a clearly defined portfolio of decision‑grade data products and standards across AGE.
• Measurable improvement in data trust indicators for priority data products over time.
• Reduction in recurrence of data trust issues through proactive monitoring and design‑time prevention.
• Delivery and scaled adoption of high‑impact AI and automation use cases, including agent‑based capabilities, enabling trusted and self‑service access to decision data.
• Measurable improvement in decision‑making efficiency and speed enabled by AI and automation (e.g., reduced manual effort, faster access to insights).

• 7+ years of relevant pharmaceutical/AI/consultant industry experience.
• Bachelor's degree required; advanced degree preferred.
• Experience defining and managing enterprise data products for decision‑making, including data quality standards, trust indicators, and governance models.
• Proven ability to establish and drive data stewardship and accountability across complex, multi‑system environments.
• Demonstrated track record of owning and driving AI, automation, or advanced analytics initiatives from identification and prioritization through to scalable adoption.
• Ability to translate AI and analytics into clear enterprise decision impact, including defining confidence signals, usage guidance, and guardrails.
• Strong ability to influence without authority and align stakeholders across business, digital, architecture, and delivery teams.
• Proven stakeholder negotiation skills, effectively managing trade‑offs (e.g., speed vs. quality, local vs. enterprise needs).
• Strong proactive problem‑solving, anticipating risks and roadblocks and driving mitigation actions across teams.
• Excellent executive communication, clearly articulating data trust, risks, confidence, and decision implications.

• Strong data and analytical literacy (e.g., SQL, Python, BI tools) and understanding of enterprise data architecture concepts.
• Experience in enterprise portfolio, R&D, or pharma decision‑making environments.
• Experience working with global teams and scaling solutions.
• Experience embedding data quality, trust, and AI readiness into system design in collaboration with architecture teams.

Salary range: $145,600 - $270,400 per year, based on relevant skills and experience. Compensation includes performance‑based incentives and eligibility for annual equity awards. Eligible U.S. employees receive a comprehensive benefits package including health, life, disability, 401(k) with company match, and a generous time‑off package comprising vacation, personal days, holidays, and other leaves.