Scientific Data Architect

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.
• Translate scientific data workflows into robust solutions leveraging the Tetra Data Platform.
• 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.

Requirements

• 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 excellent communication and storytelling abilities.
• Advised scientists in a consulting capacity to further research, development, and quality testing outcomes.
• Must be able to travel to client sites in St. Louis, Indianapolis, Chicago regions.

Nice-to-Haves / Benefits

• Competitive Salary and equity in a fast-growing company.
• Supportive, team-oriented culture of continuous improvement.
• Generous paid time off (PTO).
• Flexible working arrangements - Remote work when not at Customer Sites.