Overview As a Principal Scientist in the Systems and Disease Biology Cluster, you decode disease mechanisms at cellular resolution and pioneer AI-powered workflows that accelerate discovery to patient impact. You will lead complex cellular analytics and data science efforts to build reusable analytical templates and agentic workflows. You will coordinate projects, summarize findings for decision points in drug discovery, and mentor junior scientists when opportunities arise. This role sits at the intersection of immunology, neurology, and oncology, contributing to Sanofi's mission to deliver first-in-class medicines with cutting-edge AI support.
Compensation / Benefits- health and wellbeing benefits
- 14 weeks' gender-neutral parental leave
- career growth opportunities
- rewarding compensation package
- global mobility and international opportunities
- inclusive work environment
Responsibilities- Generate hypotheses on how targets, pathways and cell states drive diseases by integrating multi-omics and real-world data
- Apply established analytical methods to understand disease and drug mechanisms
- Design intelligent agentic workflows to deploy algorithms and models
- Lead projects involving experiment design, data analytics, and outsourcing of workflows or follow-up assays (organoid, CRISPR, proteomics)
- Collaborate with academia, industry, and internal partners on method development and disease-focused studies
- Lead and contribute to high-profile presentations and publications
- Mentor interns and junior scientists to foster a collaborative research environment
Key requirements- Ph.D. in relevant quantitative field or related biological sciences with strong data analytics/ML/AI track record
- At least 2 years of post-doctoral experience in academia or industry
- Hands-on experience with ML/AI and deploying agentic analysis workflows
- Extensive experience with multi-omics/multimodal data analysis and actionable interpretation
- Proven productivity and impact (publications or patents)
- Excellent communication and collaboration across disciplines
- communication
- organizational skills
- interpersonal skills
- ML/AI
- agentic analysis workflows
- multi-omics and multimodal data analysis
