Jobs / United States / Novartis Pharmaceuticals Corporation
Associate Director, AI & Automation Catalyst
Novartis Pharmaceuticals Corporation · 🇺🇸 2 Locations
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).
- Confirmed live todayWhen 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.
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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
Salary Range: €89,180.00 - €165,620.00 Job Description Summary #LI-Hybrid Location: Dublin, Ireland This role is based in Dublin, Ireland. Novartis is unable to offer relocation support for this role. Please only apply if this location is accessible for you. Complex data are integral to our work in clinical studies. This position is part of the Advanced Quantitative Sciences (AQS) Technology & AI function at Novartis. Our mission is to use automation and artificial intelligence to unlock the potential of complex scientific data, speed up quantitative decision-making in clinical trials, and bring innovative medicines to patients faster. Our new Statistical Computing Environment (SCE) is changing how AQS works, from how programming and QC are done in the SCE to how outputs flow across the AQS Digital workflow. The AI & Automation Catalyst turns that technology into lasting changes in daily practice. You will co-lead, with engineering and business partners, the rollout of AI and automation into the how we generate evidence. That covers redesigning processes, being a technical champion, bringing stakeholders along, and making sure new ways of working are adopted, compliant and deliver measurable value. This is a technical role and a change role, not one or the other. You are credible enough with engineers and programmers to shape solutions and challenge designs. You are also skilled enough with people to move senior stakeholders, line functions and skeptical end users from pilot to standard practice. Job Description Major accountabilities: • Leads translation of AI and automation into production. Owns the adoption roadmap for AI/automation that includes tools that span from the current-state process baseline, through future-state design and pilots, to scaled rollout. • Connects technology and business. Translates needs into clear requirements, user stories and acceptance criteria. Works hand in hand with AI & Data Engineering, SCE platform teams and IT to shape solutions. Makes informed technical trade-offs across build vs. configure, human-in-the-loop design and validation effort. • Manages stakeholders and influences without authority. Builds strong relationships across statistical programming, biostatistics, QA, line leadership and governance forums. Gets sponsors aligned, handles resistance, and turns different priorities into agreed decisions in a matrix organisation. • Redesigns processes and operating models. Redesigns QC and review workflows so AI and automation inform the standard process, and are not a bolt on. Updates SOPs, work instructions, RACI and role definitions with process owners. • Drives adoption and builds capability. Designs and runs change plans covering communications, training, champion networks, office hours and feedback loops. Tracks adoption and sentiment, and adjusts the approach based on the evidence. • Keeps change safe, compliant and inspection-ready. Understands GxP, computerised system validation and data integrity in drug development. Makes sure AI-assisted steps have the right risk assessment, human oversight, traceability and documentation. Works with QA and Compliance so the change holds up in audit. • Stays hands-on where it matters. Prototypes, reviews code and runs proofs of concept when that speeds up a decision or unblocks adoption. Offers expert guidance on complex data and automation problems. • Remains current with industry trends, and brings in external good practice on AI adoption in regulated environments through industry consortia, conferences and publications. • Fosters a culture of continuous learning, constructive challenge and innovation. Role-models transparent, responsible use of AI. Essential Requirements: • MSc or PhD in Computer Science, Data Science