Jobs / United States / Novartis Pharmaceuticals Corporation
Associate Dir, Search & Evaluation (Platforms & AI)
Novartis Pharmaceuticals Corporation · 🇺🇸 Cambridge (USA)
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 75 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Novartis Pharmaceuticals Corporation paid sponsored hires in similar roles3 certified filings for “Director, AI Use Case Lead” (Computer and Information Research Scientists) in NJ: $186k–$186k, median $186k. Most were filed at wage level III (100%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Last confirmed live 1 day agoWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
Or apply yourself on the official page →
Sponsor Radar — Novartis Pharmaceuticals Corporation
The US Department of Labor certified 75 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Novartis Pharmaceuticals Corporation →
About the role
Job Description Summary The Associate Dir, Search & Eval (Platforms & AI) is responsible for identifying, evaluating, and prioritizing external AI-enabled technologies, platforms, datasets, models, and companies that can accelerate innovation across Novartis Biomedical Research and Development. The individual will develop competitive landscapes and strategic insights across key AI use cases, conduct diligence on external opportunities by assessing scientific differentiation, technical capabilities, data quality, and strategic fit, and partner closely with internal stakeholders to shape partnering recommendations. In addition, they will support governance and leadership decision-making through opportunity assessments and landscape reviews, while also representing Novartis externally across biotech, technology, venture, academic, and industry forums. Additionally, the role will maintain a deep understanding of emerging AI trends, company landscapes, partnership activity, and competitive deal-making to identify differentiated opportunities that advance Novartis R&D priorities. This role is based in our Cambridge, MA office 3x/week. Please only apply if this works for you. Job Description Key responsibilities: • Deliver against S&E and C&BD priorities by supporting AI-focused search, landscaping, triage, and evaluation activities across R&D. • Execute structured landscapes in priority AI areas. • Conduct initial assessment and triage of inbound and proactively sourced AI opportunities, including review of technical differentiation, data assets, validation evidence, model performance, IP position, implementation requirements, and strategic fit. • Partner with internal scientific, clinical, data science, digital, legal/IP, procurement, finance, and BD&L colleagues to develop balanced opportunity assessments and identify key diligence questions. • Prepare high-quality materials for internal review and governance, including opportunity summaries, competitive landscapes, diligence updates, and recommendation slides. • Support external engagement with AI-focused companies, VCs, academic groups, and technology partners to build Novartis visibility and improve access to differentiated opportunities. • Track external deal-making, financing, technology shifts, and competitive moves in AI-enabled drug discovery and development. • Maintain organized documentation of AI landscapes, company interactions, triage rationale, and follow-up actions to support portfolio transparency and decision quality. Essential requirements: • High-quality and timely evaluation of AI-enabled R&D opportunities. • Robust landscape analyses that inform S&E priorities and governance decisions. • Effective cross-functional alignment with all relevant stakeholders. • Clear, decision-ready documentation of opportunity assessments, diligence findings, and strategic recommendations. • Strong contribution to external ecosystem coverage across AI biotech, technology companies, academia, and venture investors. • Development and maintenance of an up-to-date AI opportunity knowledge base and company tracking approach. Desirable requirements: • Advanced degree in life sciences, computational biology, chemistry, engineering, medicine, data science, or a related field strongly preferred • 5+ years of experience in biopharma R&D, AI-enabled life sciences, business development, strategy, consulting, venture, data science, computational drug discovery. • Strong understanding of drug discovery and development, with ability to evaluate how AI/ML, generative models, foundation models, knowledge graphs, lab automation, and data platforms can create R&D value. • Strong understanding of AI-enabled target discovery, chemistry, biologics, translational science, clinical d