Scientific AI Platform Lead, Data Science, Disease Area X

Location: Basel, Switzerland (Hybrid); relocation support is not available

Annual base salary: CHF 102,200–189,800

Company

hirify.global develops medicines and provides a scientific, data-driven environment focused on accelerating drug discovery.

What you will do

• Translate scientific and operational AI needs into decision-enabling solutions.
• Design, build, and sustain scalable AI-focused omics pipelines, APIs, and integrated data products.
• Scale AI workflows through reproducible, transparent, secure, and FAIR data practices.
• Establish project evaluation, deployment, lifecycle, and governance practices while prioritizing resources against research needs.
• Mentor wet lab scientists, data scientists, engineers, and cross-functional teams; oversee external vendors and service providers.
• Communicate strategy, implementation details, and results through presentations, posters, publications, and technical documentation.

Requirements

• PhD in AI/ML, data science or engineering, computational biology, bioinformatics, computer science or engineering, mathematics, physics, or a related discipline with equivalent practical experience; qualified MS applicants with 5+ years of relevant post-graduate experience are also considered.
• 3+ years of hands-on experience in scientific data science or engineering, AI/ML, or computational research within biopharma and/or the technology industry.
• Experience building and operating production-grade multimodal scientific data platforms covering omics data, data modeling, patient metadata, lineage, access controls, and reproducible workflows.
• Deep practical software or data engineering experience, including Python, SQL, version control, testing, workflow orchestration, cloud platforms, and data lakes.
• Experience leading and supporting diverse science or engineering teams and influencing stakeholders across a matrix organization.
• Strong communication, interpersonal, ethical, self-awareness, and customer service skills.
• Demonstrated scientific or technical impact through publications, conference proceedings, open-source contributions, patents, or deployed data products.

Nice to have

• Experience with genomics or transcriptomics pipelines, MCP, LLM patterns, biological foundation models, agent orchestration, and deep learning frameworks such as PyTorch.
• Familiarity with agentic frameworks such as Claude Science, Biomni, Gemini, or other open-source co-scientist platforms.
• Experience with Snowflake, Databricks, Palantir Foundry, or AWS.

Culture & Benefits

• Hybrid working options where possible, with a commitment to inclusive and diverse teams.
• Insurance plans, retirement plans, wellbeing resources, and global recognition programs.
• At least 14 weeks of paid parental leave.
• Performance-based bonus eligibility and potential group-level long-term equity awards.
• Compensation and benefits are subject to local legal requirements and may vary by country.