Scientific Business Analyst, Scientific AI- Vienna, Austria
TetraScience
- Wien
- Unbefristet
- Vollzeit
- PhD with 15+ years of industry experience in life sciences, preferably across pharma, biotech, or health tech, with deep domain expertise in discovery, preclinical, CMC, and/or Quality.
- Extensive hands-on experience or direct oversight in one or more of the following areas: high throughput screening, preclinical toxicology, materials engineering, analytical development, drug substance (DS) synthesis and manufacturing.
- Delivered requirements for AI/ML-driven solutions in operational or productized environments that improved efficiency, reduced cost, and enhanced data utilization.
- Extensive hands-on experience with scientific data workflows and lab automation; exposure to FAIR principles and modern data architecture is a plus.
- Strong coding or scripting background (e.g., Python, Nextflow, AWS, SDKs) and familiarity with scientific tools, databases, and ontologies is preferred.
- Exceptional communication and storytelling ability to engage technical and executive stakeholders.
- Prior experience in customer-facing, consulting, or commercial-scientific interface roles.
- You will be a critical team member in a unique partnership to industrialize Scientific AI. As such, you will engage directly with customers onsite up to 4-5 days per week in the Vienna Region
- Customer Data Exploration: Investigate diverse customer datasets, identifying enrichment and AI-readiness opportunities.
- Scientific Use Case Development: Collaborate with customers to define, iterate, and implement innovative scientific AI/ML use cases.
- Stakeholder Engagement: Conduct onsite interviews and workshops to deeply understand customer challenges and data landscapes.
- Data Analysis and Enrichment: Perform exploratory data analysis and define transformation workflows that enable scientific AI.
- Workflow Documentation: Develop visual documentation including workflow diagrams, ERDs, and ontology definitions.
- AI Model Evaluation: Provide practical scientific input on model output, with suggestions to improve real-world performance.
- Customer Enablement: Deliver onsite demonstrations, conduct working sessions, and act as a trusted advisor in AI adoption.
- Strategic Insight: Propose new directions, experiments, or platforms that can amplify scientific discovery and development.
- Competitive Salary and equity in a fast-growing company.
- Supportive, team-oriented culture of continuous improvement.
- Generous paid time off (PTO).
- Remote working opportunities, when not at customer sites