Director and Group Head, Applied AI
About this opportunity
Job Title: Director & Group Head (Applied AI)#LI-HybridLocation: Basel, Switzerland Relocation Support: This role is based in Basel, Switzerland. Novartis is unable to offer relocation support: please only apply if accessible.Novartis has embraced a bold strategy to drive a company-wide digital transformation. Our objective is to position Novartis as an industry leader by proactively adopting digital technologies that foster innovative approaches to hasten drug discovery and development. By utilizing both internal and external R&D data with the power of data science, predictive models, generative AI, and machine learning, our objective is to identify new targets, create more effective therapeutic molecules, better predict drug pharmacokinetics and safety risks, refine clinical trial design, and significantly shorten development cycles. The AI4R team leads BR in exploring and applying advanced AI and ML methodologies to generate novel drug discovery insights, and to speed and improve drug discovery efficiency whilst focusing on patients’ needs. AI4R partners with drug discovery teams, raises the level of AI expertise across Biomedical Research (BR) and ensures that BR science keeps up with the rapidly evolving ecosystem of AI technologies by connecting with AI leaders in academia and industry. This leadership role for the Applied AI group of AI4R will be tasked with strong technical, team and project leadership, aligning with biomedical subject matter experts to deeply understand ML opportunities in drug discovery, assessment of the model landscape, leading model benchmarking, and applying the right AI approaches, algorithms, models and workflows to maximize impact on key domains areas of biomedical research that will potentially lead to developing better drugs, faster.
Step into a pivotal leadership role at the forefront of scientific innovation, where cutting-edge artificial intelligence meets biomedical research. As Director & Group Head (Applied AI), you will shape how advanced machine learning approaches accelerate drug discovery, translating complex data into meaningful scientific insights that can transform patient outcomes. You will lead high-impact collaborations, guide strategic AI direction across research domains, and empower teams to push the boundaries of what is possible in developing better medicines, faster.Key ResponsibilitiesDefine and lead the applied artificial intelligence strategy and multi-year roadmap across drug discovery research.Align priorities with portfolio needs, scientific opportunities, and measurable business and research impact.Lead multidisciplinary teams to identify, prototype, benchmark, and deploy fit-for-purpose artificial intelligence solutions.Govern an applied artificial intelligence portfolio with clear intake, prioritization, resourcing, delivery oversight, and success metrics.Establish best practices for problem framing, data readiness, benchmarking, evaluation design, and reproducible model development.Drive benchmarking of foundation and task-specific models, enabling transparent trade-offs and informed adoption decisions.Partner with engineering teams to scale solutions and embed them into day-to-day scientific decision making.Define rigorous evaluation metrics linking model performance to downstream decisions and experimental outcomes.Build a culture of scientific rigor, rapid iteration, mentorship, and practical impact across teams.Forge strategic academic and industry collaborations to accelerate innovation, benchmarking, and technology transfer.Essential RequirementsDemonstrated experience in leading core machine learning capability development initiatives across drug discovery teams and use cases.Proven experience with foundation model benchmarking in drug discovery applications.Hands-on experience applying machine learning to core drug discovery areas such as target identification or computational chemistry.Strong experience in large-scale model training, distributed computation, model adaptation, and deployment within machine learning operations frameworks.Deep curiosity and passion for biomedical sciences and therapeutic discovery, with ability to explain complex technical concepts clearly.Minimum of 12+ years of experience in innovation, development, deployment, and continuous support of machine learning and modeling solutions.Strong coding proficiency in Python and deep learning frameworks, with experience using version control systems such as Git.Ability to manage complexity, balance priorities, and drive outcomes effectively within matrixed environments using a proactive mindset.Desirable RequirementsPublications, patents, or open-source contributions demonstrating machine learning innovation and domain expertise.Strong curiosity for emerging technologies with pragmatic ability to apply them to real-world business challenges.Commitment to Diversity and InclusionNovartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.Accessibility and AccommodationNovartis is committed to working with and providing reasonable accommodation to all individuals. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or to receive more detailed information about the essential functions of a position, please email [email protected] and share the nature of your request along with your contact information. Please include the job requisition number in your message.
Job details
How this role compares
Computed from every other active Data & Digital role in our database, not just this employer's listings.
We currently track 34 comparable Director Data & Digital roles across 15 biopharma companies.
Salary context
16 of 34 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 34 comparable roles
Seniority mix
34 of 34 peers have a known seniority level
Therapeutic area mix
3 of 34 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.