Scientific Data Architect
Designs and implements scalable scientific data models, pipelines, integrations, applications, and AI-driven solutions for biopharma customers. The role requires substantial life sciences domain experience, strong data architecture and Python skills, customer engagement, and collaboration across scientific, product, and engineering teams.
About the job
Responsibilities
- Engage directly with customers onsite a couple of days per week in the assigned geographic region to understand scientific data challenges and requirements and accelerate solutions.
- Design and implement extensible, reusable data models that capture and organize scientific data for scalability and future adaptability.
- Translate scientific data workflows into robust solutions using the Tetra Data Platform.
- Own, scope, prototype, and implement solutions including:
- Data model design
- Python-based pipeline development
- Lab software integrations, such as ELN/LIMS, via APIs
- Data visualization and application development
- Scientific agents
- Use agentic development tools such as Claude Code and Codex for discovery, prototyping, and development.
- Collaborate with Scientific Business Analysts, customer scientists, and applied AI engineers to develop and deploy ML, AI, mechanistic, statistical, and hybrid models and agents.
- Interface directly with scientific end users and technical stakeholders through regular demos and meetings to drive solution development and adoption.
- Communicate implementation progress and deliver demos to customer stakeholders.
- Collaborate with the product team to build and prioritize the roadmap based on customer pain points.
- Rapidly learn new technologies to develop and troubleshoot use cases.
- Travel to client sites in local geographic areas.
Requirements
- PhD with 4+ years, master's degree with 6+ years, or bachelor's degree with 8+ years of industry experience in life sciences.
- Extensive domain knowledge in drug discovery, preclinical development, CMC, product quality testing, or pharmaceutical manufacturing.
- Proven experience defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments.
- Experience designing scalable and reusable data architecture.
- Experience collaborating with product managers, software engineers, and scientific stakeholders.
- Experience performing exploratory data analysis and workflow optimization.
- Excellent communication and storytelling skills for engaging scientists and executive stakeholders.
- Experience advising scientists in a consulting capacity.
- Experience augmenting technical, business, and communication work through agentic development and knowledge work.
Nice to Have
- Hybrid dry-lab and wet-lab experience.
Compensation and Benefits
- Salary range: $140,000–$240,000.
- 100% employer-paid benefits for eligible employees and immediate family members.
- Unlimited paid time off.
- 401(k).
- Company-paid life insurance and LTD/STD.
- Continuous-improvement culture with career growth and coaching.
- Visa sponsorship is not currently provided.
Skills
Python, Data Architecture, Data Modeling, Machine Learning, Artificial Intelligence, Cloud Computing, Exploratory Data Analysis, Eln/Lims, APIs, Data Visualization, Scientific Agents, Claude Code, Codex, Drug Discovery, Pharmaceutical Manufacturing
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