Associate Dir, Search & Evaluation (Platforms & AI)

In this role, you identify and assess external AI-enabled technologies and partnerships to accelerate Novartis R&D. You’ll build competitive landscapes, run diligence on scientific and technical differentiation, and shape partnering recommendations with internal stakeholders. You’ll support governance and leadership decisions, stay ahead of AI trends, and represent Novartis externally to biotech, tech, and academic communities. The position sits in Cambridge, MA with a 3x/week on-site requirement and offers exposure to high-impact AI-enabled drug discovery initiatives.

• health, life and disability benefits
• 401(k) with company contribution and match
• equity eligibility potential
• comprehensive benefits package
• generous time off package (vacation, personal days, holidays)
• performance-based cash incentive

• Support AI-focused search, landscaping, triage, and evaluation across R&D to drive S&E and BD priorities
• Create structured landscape analyses in priority AI areas
• Perform initial triage of inbound and proactive AI opportunities, evaluating differentiation, data, model performance, IP, implementation needs, and strategic fit
• Collaborate with scientists, data scientists, digital, legal/IP, procurement, finance, and BD&L to develop balanced opportunity assessments
• Prepare governance-ready materials, including summaries, landscapes, diligence updates, and recommendations
• Engage with external AI-focused companies, VCs, academia, and technology partners to boost visibility and deal access
• Monitor external AI deal activity and competitive moves relevant to drug discovery and development
• Maintain organized documentation on AI landscapes, interactions, rationale, and follow-ups for portfolio transparency

• High-quality, timely evaluation of AI-enabled R&D opportunities
• Robust landscape analyses informing S&E priorities and governance
• Strong cross-functional alignment with stakeholders
• Clear, decision-ready documentation of assessments and recommendations
• Active contribution to external ecosystem coverage in AI biotech, technology, academia, and venture
• Up-to-date AI opportunity knowledge base and company tracking

• Cross-functional collaboration
• Clear communication
• Strategic synthesis of diverse inputs
• AI/ML evaluation and due diligence
• Generative models and foundation models
• Knowledge graphs and data platforms