Scientific Data Architect- Central US

About the role

TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world's leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing.

Requirements

• What You Will Do:
  • Engage directly with customers onsite a couple of days per week in the Indianapolis area, building strong relationships, deeply understanding their scientific data challenges and requirements, and accelerating solutions.
  • Design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and future adaptability.
  • Own, scope, prototype, and implement solutions including: Data model design (tabular & JSON), Python-based parser development, Lab software (e.g., ELN/LIMS) integration via APIs, Data visualization and app development in Python (using app frameworks like Streamlit and plotting tools like holoviews and Plotly).
  • Collaborate with Scientific Business Analysts (SBAs), customer scientists and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid).
  • Programmatically interrogate proprietary instrument output files.
  • Dynamically iterate with scientific end users and technical stakeholders to rapidly drive solution development and adoption through regular demos and meetings.
  • Proactively communicate implementation progress and deliver demos to customer stakeholders.
  • Collaborate with the product team to build and prioritize our roadmap by understanding customers' pain points within and outside Tetra Data Platform.
  • Rapidly learn new technologies (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases.

Qualifications

• PhD with +4 years or Masters with +8 years of industry experience in life sciences with extensive domain knowledge in drug discovery (target ID through lead optimization), preclinical development, CMC (all drug modalities), or product quality testing.
• Proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments.
• Collaborated with cross-functional teams, including product managers, software engineers, and scientific stakeholders.
• Performed extensive exploratory data analysis and workflow optimization to enable scientific outcomes not previously possible.
• Engaged diverse audiences, from scientists to executive stakeholders using your excellent communication and storytelling abilities.
• Advised scientists in a consulting capacity to further research, development, and quality testing outcomes.