The job, in the employer's words
About TetraScience
TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.
In connection with your candidacy, you will be asked to carefully review “The Tetra Way,”
authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you.
Who You Are
You are a product-minded, outcome-obsessed driver of technical scientific solutions.
You are a high velocity self-starter. You refuse to let uncertainty obstruct your path to designing and building solutions.
You roll up your sleeves, try things out, and get things done. You do not hesitate to prototype, demo, and build in order to accelerate delivery of products for your end users.
You thrive in environments where you can collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes. Your ability to engage with scientists and business leaders alike makes you a key player in maximizing the value of scientific data.
With rich experience applying cutting edge data methodologies to the biopharma R&D domain, you bridge understanding between present-day pain points and generalizable solutions.
You are an insatiable learner, with a track record of deeply learning new tools, methods, and domains.
You fundamentally embody the principles of extreme ownership and have a demonstrated history of building extensible data models and applications for Biopharma end users to maximize value from their data via analysis and integration with AI/ML.
This role will require extreme self-discipline and determination as we forge a category that will fundamentally and forever change the life science industry.
Requirements
What You Have Done
You deeply understand the life science R&D data ecosystem – you’ve felt the pain of brittle, bespoke workflows with fractured data, and you’ve actively worked to solve this. In our experience, the candidates with this experience bring the following background:
- PhD with +4 years, Masters with +6 years, or Bachelors 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), product quality testing, or pharma manufacturing.
- Proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments
- Designed scalable and reusable data architecture
- 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.
- Engage 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.
- Augmented your technical, business, and communication work through agentic development and knowledge work
- Nice to have: Hybrid dry lab / wet lab experience
What You Will Do
- You will be a critical team member in a unique partnership to industrialize Scientific AI. As such, you will engage directly with customers onsite a couple of days per week in the assigned geographic region, 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
- Python-based pipeline development.
- Lab software (e.g., ELN/LIMS) integration via APIs.
- Data visualization and app development
- Scientific agents
- Leverage agentic development tools like Claude Code and Codex to contribute to discovery, prototyping, and development
- Collaborate with Scientific Business Analysts (SBAs), customer scientists and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid) and agents
- Interface directly 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 to develop and troubleshoot use cases
- Must be able to travel to client sites in local geographic areas
Benefits
- 100% employer-paid benefits for all eligible employees and immediate family members
- Unlimited paid time off (PTO)
- 401K
- Company paid Life Insurance, LTD/STD
- A culture of continuous improvement where you can grow your career and get coaching
We are not currently providing visa sponsorship for this position.
The salary range for this position is $140,000 - $240,000. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.
Benefits mentioned
- 100% employer-paid benefits for all eligible employees and immediate family members
- Unlimited paid time off (PTO)
- 401K
- Company paid Life Insurance, LTD/STD
- A culture of continuous improvement where you can grow your career and get coaching
- We are not currently providing visa sponsorship for this position.
- The salary range for this position is $140,000 - $240,000. The salary range posted reflects our target baseline for this role. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity.
Requirements mentioned
- You are a product-minded, outcome-obsessed driver of technical scientific solutions.
- You are a high velocity self-starter. You refuse to let uncertainty obstruct your path to designing and building solutions.
- You roll up your sleeves, try things out, and get things done. You do not hesitate to prototype, demo, and build in order to accelerate delivery of products for your end users.
- You thrive in environments where you can collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes. Your ability to engage with scientists and business leaders alike makes you a key player in maximizing the value of scientific data.
- With rich experience applying cutting edge data methodologies to the biopharma R&D domain, you bridge understanding between present-day pain points and generalizable solutions.
- You are an insatiable learner, with a track record of deeply learning new tools, methods, and domains.
- You fundamentally embody the principles of extreme ownership and have a demonstrated history of building extensible data models and applications for Biopharma end users to maximize value from their data via analysis and integration with AI/ML.
- This role will require extreme self-discipline and determination as we forge a category that will fundamentally and forever change the life science industry.
- You deeply understand the life science R&D data ecosystem – you’ve felt the pain of brittle, bespoke workflows with fractured data, and you’ve actively worked to solve this. In our experience, the candidates with this experience bring the following background:
- PhD with +4 years, Masters with +6 years, or Bachelors 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), product quality testing, or pharma manufacturing.
- Proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments
- Designed scalable and reusable data architecture
- 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.
- Engage 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.
- Augmented your technical, business, and communication work through agentic development and knowledge work
- Nice to have: Hybrid dry lab / wet lab experience
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