This role is at the nexus of science, data, and software innovation. As a Scientific Business Analyst, you will work directly with scientists, engineers, and product teams to unlock the potential of scientific data in life sciences R&D and Quality settings. Your primary mission is to interpret complex scientific processes and convert them into clear, data-driven requirements that power AI and machine learning applications.
Key Responsibilities
- Partner with cross-functional teams to identify high-impact use cases in drug discovery, preclinical development, CMC, and Quality
- Translate scientific workflows into structured data needs and system requirements
- Engage directly with customers on-site to understand challenges and co-develop solutions
- Define specifications for advanced data systems that serve scientific personas
- Ensure technical solutions align with scientific accuracy and business objectives
- Drive data enrichment and integration strategies that maximize AI readiness
- Take full ownership of data outcomes, from analysis to implementation
What You Bring
- Strong background in life sciences, with deep familiarity in drug discovery, CMC, or Quality domains
- Proven ability to communicate effectively with both technical and non-technical stakeholders
- Experience turning scientific processes into software-aware data requirements
- Fluency in data systems and a forward-thinking mindset aligned with AI-driven transformation
- Commitment to working on-site with customers to build trust and deliver impact
- Demonstrated success in extracting value from scientific data through analysis and integration
Environment and Impact
You’ll operate in a fast-moving, high-ownership culture focused on scientific advancement. This is a frontline role in shaping how AI interprets and enhances laboratory data. You’ll collaborate with leaders in cloud computing, data infrastructure, and AI, contributing to the industrialization of next-generation scientific datasets. The work directly influences how life sciences organizations achieve AI-enabled outcomes, with real-world impact on research efficiency and quality.
Work Model
This is an onsite position based in Basel, Switzerland, with regular customer visits required. The role demands face-to-face engagement to build deep relationships and ensure successful adoption of data-driven solutions.
