Scientific Data Architect - Central US
About The Position
TetraScience is hiring a Scientific Data Architect to help life sciences organizations turn fragmented scientific data into AI-native assets and workflows. The role is part of a partnership to industrialize Scientific AI and involves working directly with customers in the assigned geographic region to understand their scientific data challenges, build relationships, and accelerate solutions. The position requires regular onsite customer engagement and travel to client sites in local geographic areas 3–4 days per week. The Scientific Data Architect designs and implements extensible, reusable data models and translates scientific data workflows into solutions using the Tetra Data Platform. The role includes scoping, prototyping, and implementing data models, Python pipelines, integrations with laboratory software such as ELN/LIMS through APIs, data visualizations and applications, and scientific agents. The architect collaborates with scientific business analysts, customer scientists, applied AI engineers, product managers, software engineers, and other stakeholders to develop and deploy AI, machine learning, mechanistic, statistical, and hybrid models and agents. The position also supports solution adoption through regular meetings and demos, communicates implementation progress, contributes to product-roadmap prioritization, and learns new technologies to develop and troubleshoot use cases. The company describes its culture as emphasizing extreme ownership, self-discipline, continuous improvement, rapid learning, and taking initiative to prototype and deliver solutions. TetraScience asks candidates to review “The Tetra Way” as part of their candidacy. Visa sponsorship is not currently provided for this position.
Requirements
- PhD with more than 4 years, Master’s degree with more than 6 years, or Bachelor’s degree with more than 8 years of industry experience in life sciences.
- Extensive domain knowledge in drug discovery (target identification through lead optimization), preclinical development, CMC across drug modalities, product quality testing, or pharmaceutical manufacturing.
- Proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments.
- Experience designing scalable and reusable data architecture.
- Experience collaborating with cross-functional teams, including product managers, software engineers, and scientific stakeholders.
- Experience performing exploratory data analysis and workflow optimization to enable scientific outcomes.
- Excellent communication and storytelling abilities to engage audiences ranging from scientists to executive stakeholders.
- Experience advising scientists in a consulting capacity to improve research, development, and quality-testing outcomes.
- Experience augmenting technical, business, and communication work through agentic development and knowledge work.
- Ability to travel to client sites in local geographic areas 3–4 days per week.
- Visa sponsorship is not available for this position.
Nice To Haves
- Hybrid dry lab and wet lab experience.
Responsibilities
- Engage directly with customers onsite in the assigned geographic region to build relationships, understand scientific data challenges and requirements, and accelerate solutions.
- Design and implement extensible, reusable data models that organize scientific data for use cases while supporting scalability and future adaptability.
- Translate scientific data workflows into robust solutions using the Tetra Data Platform.
- Own, scope, prototype, and implement solutions involving data model design, Python-based pipeline development, laboratory software integrations via APIs, data visualization and application development, and scientific agents.
- Use agentic development tools such as Claude Code and Codex to support discovery, prototyping, and development.
- Collaborate with Scientific Business Analysts, customer scientists, and applied AI engineers to develop and deploy machine learning, AI, mechanistic, statistical, and hybrid models and agents.
- Interface with scientific end users and technical stakeholders to drive solution development and adoption through regular demos and meetings.
- Communicate implementation progress proactively and deliver demos to customer stakeholders.
- Collaborate with the product team to understand customer pain points and build and prioritize the product roadmap.
- Learn new technologies to develop and troubleshoot use cases.
- Travel to client sites in local geographic areas 3–4 days per week.
Benefits
- 100% employer-paid benefits for eligible employees and immediate family members.
- Unlimited paid time off (PTO).
- 401(k).
- Company-paid life insurance.
- Company-paid long-term and short-term disability insurance (LTD/STD).
- A culture of continuous improvement with opportunities to grow your career and receive coaching.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
