Salary Range:

CHF78,400.00 - CHF145,600.00

 

Band

Level 3

 

Job Description Summary

The Scientific AI Platform Expert will join the Disease Area X (DAx) Data Science team at Novartis to build enterprise-grade, AI analysis platforms and data products to accelerate drug discovery. This role will lead and partner on multidisciplinary project teams, operationalize generative and agentic AI solutions, contribute to shaping DAx AI data strategy, and collaborate with enterprise IT teams. This role reports to the Head of Data Science, DAx.

 

Job Description

Internal job title:  Expert I/II, Data Science 

Position Location: Basel, CH, Hybrid

 

** This role is based in Basel, CH. Novartis is unable to offer relocation support for this role: please only apply if this location is accessible for you. 

 

Job description Summary:

 

The Scientific AI Platform Expert will join the Disease Area X (DAx) Data Science team at Novartis to build enterprise-grade, AI analysis platforms and data products to accelerate drug discovery. This role will lead and partner on multidisciplinary project teams, operationalize generative and agentic AI solutions, shape DAx AI data strategy, and collaborate with enterprise IT teams. This role reports to the Head of Data Science, DAx.

 

Key Responsibilities:

• Translate scientific and operational AI needs into impactful, decision-enabling solutions.
• Hands-on design, build, and sustain scalable AI-focused omics pipelines, APIs, and integrated data products.
• Scale AI workflows using reproducible, transparent, secure, and FAIR data practices.
• Prioritize resources against evolving research needs.
• Provide input to the team on project evaluation, deployment, lifecycle, and governance practices.
• Assist as needed with the onboarding of external vendors and service providers.
• Effectively provide input to the team on strategy, implementation details and results through internal and external presentations, posters, publications, and technical documentation.

Essential Requirements:

• BS or MS in AI/ML, data science/engineering, computational biology, bioinformatics, computer science/engineering, mathematics, physics, or a related discipline, with 3+ years of hands-on experience in scientific data science or engineering, AI/ML, computational research within the biopharma and/or technology industry. We will also consider qualified recent PhD graduates (within last 2 years).
• Experience building and operating production-grade multimodal data platforms for scientific analysis: omics data, data modeling, patient metadata, lineage, access controls, and reproducible workflows.
• Experience with omics analysis pipelines (i.e. genomics, transcriptomics), MCP, LLM patterns, biological foundational models, agent orchestration, and deep learning frameworks (i.e. Pytorch) is preferred.
• Familiarity with current agentic frameworks such Claude Science, Biomni, Gemini or other open-source co-scientist platforms.
• Deep practical experience in software or data engineering (i.e. agile), including Python, SQL, version control, testing, workflow orchestration, cloud platforms, and data lakes (i.e. Snowflake, Databricks, Palantir Foundry, AWS).
• Strong communication, interpersonal, ethical, self-awareness, and customer service skills.

Desired Requirements:

• Demonstrated record of scientific or technical impact through publications, conference proceedings, open-source contributions, patents, or deployed data products.
• Experience leading and supporting cross-functionally across diverse science or engineering teams, influencing key stakeholders across a matrix organization.

Benefits & Rewards: 

At Novartis, we’re committed to reimagining medicine together - and rewarding the people who make it happen. 

  

Expected Annual Base Salary Range for role: CHF 78,400 - CHF 145,600

  

The base 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. 

  

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 minimum 14 weeks paid parental leave. 

In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters. Long-term equity awards granted at group level may also be part of your package. Further details will be provided during the application process.  

  

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:

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Accessibility and Accommodation:

Novartis 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 in order to receive more detailed information about the essential functions of a position, please send an e-mail to diversity.inclusion_ch@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message. 

 

Skills Desired

Artificial Intelligence (AI), Biostatistics, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Generative AI, Graph Algorithms, Learning Agility, Logistic Regression Models, Machine Learning (ML), Machine Learning Algorithms, Neuro-Linguistic Programming (NLP), Pandas Python Library, Python (Programming Language), R Programming, Statistical Analysis, Structured Query Language (SQL), Time Series Analysis