Scientific Data Architect

TetraScience

Critical team member industrializing Scientific AI through customer engagement and data modeling. Designing extensible data models and solutions for scientific data challenges at TetraScience.

Posted 5/20/2026full-timeIndianapolis • 🇺🇸 United StatesSeniorLeadWebsite

Tech Stack

Tools & technologies

AWSCloudPython

About the role

Key responsibilities & impact

You will be a critical team member in a unique partnership to industrialize Scientific AI.
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 interrogating 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.
Must be able to travel to client sites in St. Louis, Indianapolis, Chicago regions.

Requirements

What you’ll need

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.

Benefits

Comp & perks

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**

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data model designPythondata visualizationapp developmentAPI integrationmachine learningartificial intelligencedata analysisworkflow optimizationprototyping

Soft Skills

communicationcollaborationrelationship buildingproblem solvingstorytellingconsultingadaptabilitycustomer engagementteamworkstakeholder management

Certifications

PhDMasters