Senior Expert Data Science & AI (Low Molecular Weight Drug Discovery)

Key Responsibilities

• Lead 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 Requirements

• 4+ 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 Requirements

• Experience 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.

Rewards

At 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 Annual

The 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.