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TetraScience is building Tetra OS, an operating system for scientific intelligence that helps life sciences firms transform fragmented scientific data into AI-native assets and scientific workflows. The company partners with industry leaders including NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.
You will be a critical team member in industrializing Scientific AI, engaging directly with customers onsite (up to 25% travel) to build strong relationships, deeply understand their scientific data challenges, and accelerate solutions. You will design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and future adaptability.
Key responsibilities include:
- 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 (ELN/LIMS) integration via APIs, and data visualization/app development in Python (Streamlit, holoviews, Plotly)
- Programmatically interrogate proprietary instrument output files
- Collaborate with Scientific Business Analysts, customer scientists, and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid)
- Dynamically iterate with scientific end users and technical stakeholders through regular demos and meetings
- Proactively communicate implementation progress and deliver demos to customer stakeholders
- Collaborate with the product team to build and prioritize the roadmap by understanding customers' pain points
- Rapidly learn new technologies (AWS services, scientific analysis applications) to develop and troubleshoot use cases
You are a product-minded, outcome-obsessed driver of technical scientific solutions. You are a high-velocity self-starter who refuses to let uncertainty obstruct your path to designing and building solutions. You roll up your sleeves, prototype, demo, and build to accelerate delivery. You thrive collaborating with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes. You are an insatiable learner with a track record of deeply learning new tools, methods, and domains. You fundamentally embody extreme ownership and have demonstrated history of building extensible data models and applications for Biopharma end users.
REQUIREMENTS:
- PhD with 4+ years OR Master's degree with 8+ years of industry experience in life sciences
- 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
- Demonstrated collaboration with cross-functional teams including product managers, software engineers, and scientific stakeholders
- Experience performing extensive exploratory data analysis and workflow optimization to enable scientific outcomes
- Excellent communication and storytelling abilities to engage diverse audiences from scientists to executive stakeholders
- Experience advising scientists in a consulting capacity to further research, development, and quality testing outcomes
- No visa sponsorship available for this position
