Senior Expert Data Science & AI (Low Molecular Weight Drug Discovery)
About this opportunity
Job Title: Senior Expert Data Science & AI (Low Molecular Weight Drug Discovery)#LI-HybridLocation: Dublin, IrelandRelocation Support: This role is based in Dublin, Ireland. Novartis is unable to offer relocation support: please only apply if accessible.Step into a role where cutting-edge AI meets life-changing science, drive breakthroughs in drug discovery by shaping how intelligent systems design the next generation of therapeutics. As a Senior Expert in Data Science & AI, you will lead the development and application of advanced AI methodologies to accelerate low molecular weight drug discovery, collaborating with world-class scientists to transform complex biomedical challenges into innovative, data-driven solutions that ultimately improve patient outcomes.
Key ResponsibilitiesLead technical strategy for artificial intelligence in low molecular weight drug discovery programs.Evaluate emerging model landscapes and identify opportunities for methodological innovation with measurable scientific impact.Design, build, and benchmark algorithms, models, and workflows for hit generation and lead optimization.Translate model performance into decision-ready metrics that improve prioritization, assays, and experimental efficiency.Partner with engineering and product teams to deliver scalable artificial intelligence solutions into research workflows.Collaborate with scientists across medicinal chemistry, structural biology, and disease biology to accelerate design-test-learn cycles.Advance automation by developing agentic workflows for computer-aided drug design pipelines.Guide model robustness and performance with strong validation and close alignment to experimental follow-up.Drive high-value collaborations across Biomedical Research and strengthen artificial intelligence adoption across research teams.Communicate progress, insights, and portfolio impact to leadership to position artificial intelligence as a discovery accelerator.Essential Requirements4+ years of experience in machine learning innovation, development, deployment, and model lifecycle management.Proven experience applying machine learning to drug discovery, including generative models and molecular design.Strong proficiency in Python and deep learning frameworks for model development and experimentation.Solid understanding of version control systems such as Git for collaborative software development.Demonstrated expertise in structure-based drug design, including docking, scoring, and pose evaluation.Experience integrating artificial intelligence models with experimental workflows in lab-in-the-loop environments.Ability to design robust, validated models with clear connections to downstream scientific decision-making.Strong collaboration, problem-solving, and communication skills in complex, matrixed environments.Desirable RequirementsExperience working in large global pharmaceutical or biomedical research organizations with complex data ecosystems.Awareness of emerging artificial intelligence methodologies such as foundation models, explainability, and geometric deep learning.RewardsAt Novartis, we’re committed to reimagining medicine together - and rewarding the people who make it happen.The rewards of being part of our team go far beyond base pay and incentives. We also offer a variety of competitive benefits in kind to help you thrive personally and professionally, such as insurance plans, retirement plans, wellbeing resources and global recognition programs. In addition, we provide flexible and hybrid working options, where possible, and a minimum of 14 weeks paid parental leave.Expected Annual Base Salary Range for role:Dublin: 63,490.00- 117,910.00 EUR AnnualThe salary offered is determined based on gender-neutral objectives, such as relevant skills, competencies and experience in accordance with the Novartis pay setting policy and upon joining Novartis will be reviewed periodically.In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters. Further details will be provided during the application process.Pay equity is a fundamental principle of our employment policy and reflects our commitment to create a diverse, equitable and inclusive environment that treats all employees with dignity and respect, as outlined in our Code of Ethics.Read our brochure to learn more about our global total rewards offering: https://www.novartis.com/sites/novartis_com/files/novartis-life-handbook.pdf Note: Benefits and compensation may vary by country and are subject to local legal requirements, including provisions of collective bargaining agreements where applicable. A full overview of your compensation package, including any relevant collective bargaining agreement details applicable to your role based on your employment location and Novartis employer entity, will be communicated separately to you during the application process. Commitment to Diversity and Inclusion / EEO paragraph:Novartis is committed to building an outstanding, inclusive work environment and diverse teams’ representative of the patients and communities we serve.
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 92 comparable Senior Data & Digital roles across 23 biopharma companies.
Salary context
16 of 92 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 92 comparable roles
+ 7 more countries
Seniority mix
92 of 92 peers have a known seniority level
Therapeutic area mix
2 of 92 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.