Scientific Business Analyst, Cheminformatics

TetraScience
Cambridge, MA

Who We Are

TetraScience is the Scientific Data and AI company. We are catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next gen lab data management solutions, scientific use cases, and AI-enabled outcomes. 

TetraScience is the category leader in this vital new market, generating more revenue than all other companies in the aggregate. In the last year alone, the world’s dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships: Latest News and Announcements | TetraScience Newsroom

We are committed to accelerating discovery and development by engineering liquid, contextualized, FAIR data, and enabling AI-native scientific outcomes. Our Scientific Business Analysts (Sciborgs) are a bridge between scientists and data engineers, translating complex R&D requirements into actionable data and AI solutions that transform how science is done.

As part of our high-profile partnership with a top pharma company, we are building a team of chemistry-focused Sciborgs who will bring domain expertise in medicinal chemistry, synthetic chemistry, and DMPK/metabolite ID to the forefront of scientific data transformation

In connection with your candidacy, you will be asked to carefully review the Tetra Way letter, authored directly by Patrick Grady, our co-founder and CEO. This letter is designed to assist you in better understanding whether TetraScience is the right fit for you from a values and ethos perspective. 

It is impossible to overstate the importance of this document and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents each day. 

Who You Are

We are seeking a Scientific Business Analyst – Cheminformatics with a strong foundation in synthetic or medicinal chemistry and experience working with data platforms, cheminformatics tools, and workflow automation. This role is ideal for someone who has: 

  • Been at the bench or in a med chem team, has curated or managed chemical/assay data, and is excited to translate scientific requirements into technical specifications for data architects, engineers, and AI teams.
  • You will work directly with our partner’s scientists and TetraScience’s engineering teams to harmonize, contextualize, and enable advanced analytics on critical chemistry and DMPK datasets.

What You'll Do

  • Serve as the bridge between medicinal chemists/DMPK scientists and technical teams, gathering requirements and translating them into clear specifications for data engineers and AI solution developers.
  • Partner with our partner’s med chem teams on DMTA (design-make-test-analyze) cycles, ensuring scientific data flows seamlessly between compound design, assay results, and decision-making workflows.
  • Map and harmonize scientific data across key platforms: LiveDesign (Schrödinger) for compound design and tracking.D360 for SAR analysis, data visualization, and activity cliffs. KNIME for no-code workflow automation and plate map generation. Internal databases (grdb) and other informatics tools. Identify and resolve data comparability challenges across sites/vendors (e.g., assay reproducibility, sequential vs. parallel execution).
  • Collaborate with upstream (biology/target validation) and downstream (DMPK, safety, analytical) functions to ensure chemistry data is contextualized for cross-domain integration.
  • Support adoption of new tools and platforms (e.g., CDD Vault, StarDrop, Genedata, Pipeline Pilot, Spotfire) by defining requirements, building prototypes, and driving user feedback loops.
  • Develop user stories, workflows, and data models that guide engineering teams in building scalable solutions for chemistry data and AI/ML applications.

What You Bring

  • PhD or MS in Organic Chemistry, Cheminformatics, Medicinal Chemistry, or related field with 3+ years of post-graduate industry experience (med chem, DMPK, or analytical).
  • Hands-on experience in synthetic chemistry or medicinal chemistry with exposure to DMTA workflows and data-driven decision-making.
  • Familiarity with cheminformatics and scientific data tools such as LiveDesign, D360, KNIME, Pipeline Pilot, Spotfire, CDD Vault, StarDrop, Genedata.
  • Ability to understand and communicate both scientific and technical concepts, including assay design, SAR analysis, plate-based workflows, and LC-MS data.
  • Strong skills in data curation, pipeline development, and workflow automation; exposure to SQL or Python preferred. Excellent problem-solving and communication skills; able to partner with both bench scientists and data engineers.
  • Passion for enabling AI/ML solutions in drug discovery and development.
  • Experience performing extensive exploratory data analysis and workflow optimization to enable scientific outcomes not previously possible.
  • Ability to engage diverse audiences, from scientists to executive stakeholders using your excellent communication and storytelling abilities
  • Experience advising scientists in a consulting capacity to further research, development, and quality testing outcomes.

Why Tetrascience

Join a mission-driven company transforming the scientific data ecosystem. Be part of a high-impact partnership with a top 25 pharma, helping to shape how modern medicinal chemistry integrates with AI. Collaborate with world-class scientists, engineers, and AI experts. Competitive compensation, comprehensive benefits, and career growth opportunities.

Benefits

  • 100% employer-paid benefits for all eligible employees and immediate family members
  • Unlimited paid time off (PTO)
  • 401K
  • Remote working opportunities, when not at customer sites
  • Company paid Life Insurance, LTD/STD
  • A culture of continuous improvement where you can grow your career and get coaching
Posted 2025-11-12

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