Scientific Solutions Partner- Central US
- Compensation
- Not disclosed
- Location
- Indianapolis, Indiana, United States; Chicago, Illinois, United States; St. Louis, Missouri, United States
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Sales
- Posted
Skills
Must have
- A Bachelors in a life science, chemistry, or engineering discipline required. A MS or PhD is highly preferred; equivalent practical experience considered
- 5+ years of combined scientific, technical, and commercial experience in life sciences software, laboratory informatics, scientific data infrastructure, or adjacent domains
- Direct experience in pharma, biotech, or CRO/CDMO environments — either as a scientist, scientific software professional, or sales/solutions professional serving these customers
- Demonstrated ability to lead technical sales cycles in enterprise SaaS or scientific software, including POC design and execution and RFP ownership
- Deep familiarity with laboratory workflows and data: you understand what it means when a customer has 50 instruments generating unstructured data that no one can analyze
- Fluency with scientific data concepts: file formats, instrument connectivity, data harmonization, and the path from raw data to AI-ready datasets
- Experience with modern sales methodologies (MEDDIC, MEDDPIC, Force Management, or similar)
- Strong executive presence — equally compelling in a whiteboard architecture session and a C-suite business case conversation
- Proficiency with CRM and digital sales tools (Salesforce, LinkedIn Sales Navigator, ZoomInfo, SalesLoft, or equivalent)
- Ability to travel (approximately 25%) to client sites within assigned region
Full description
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.
The Role
The Scientific Solutions Partner is a new role born from a deliberate strategic choice: the most effective way to sell TetraScience’s Scientific Data and AI Cloud is to have one person who can credibly do both — win the scientific and technical confidence of the customer and manage the commercial relationship to close. No separate Account Executive needed.
This is not a traditional Account Executive role with a presales overlay. The Scientific Solutions Partner owns the full customer engagement, from prospecting and discovery through technical solutioning, proof-of-concept, RFP response, and close — and remains accountable for the account’s health, expansion, and renewal alongside the Delivery Manager. Both roles share accountability for identifying and progressing expansion opportunities within their accounts.
You will work with the world's largest enterprise biopharma, biotech, and life sciences companies, helping them understand how the Tetra Scientific Data Foundry and Tetra OS transforms siloed, raw scientific data into AI-ready scientific datasets across the medallion architecture (bronze → silver → gold → AI-native). You will engage audiences ranging from bench scientists and data engineers to CDOs, VPs of Divisional IT, VPs of Scientific areas, and digital transformation executives.
TetraScience provides its SSPs with AI-powered tools — including Claude Cowork and Codex — that automate RFPs, triage, and contracting workflows, enabling each SSP to operate with the leverage of a larger team.
What You’ll Do
Scientific & Technical Engagement
- Lead technical discovery: understand the customer’s current lab data landscape — instruments, data formats, informatics stack, and data science ambitions
- Design and present compelling solution architectures aligned to the customer’s specific scientific use cases (e.g., ADMET assays, FPLC/UPLC chromatography, bioassay data harmonization, AI training datasets) as well as understanding their core data management pain points and goals.