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TetraScience

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Scientific Solutions Partner - Copenhagen, Denmark

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.

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.

● Always be leading with demo’s of actual software aligned to the customers main value levers.

● Own and drive proof-of-concept and proof-of-value engagements, partnering with TetraScience scientific data architects to deliver credible, high-quality demonstrations of the Tetra Scientific Data Foundry’s capabilities

● Own RFP technical responses end-to-end, synthesizing platform capabilities, scientific use cases, and customer-specific requirements into compelling, accurate submissions

● Articulate the medallion data architecture in scientific and business terms: how bronze (raw scientific data), silver (harmonized Tetra Data), and gold (analysis-ready datasets) each create value, and how TetraScience’s AI-native layer accelerates scientific outcomes

● Stay current on the scientific and informatics landscape — relevant assay workflows, instrument vendors, SDMS/ELN/LIMS/analytical software integrations, and AI/ML use cases in drug discovery and development

Commercial Ownership

● Prospect, qualify, and build territory pipeline in alignment with the TetraScience go-to-market strategy

● Relentlessly identify and close expansion opportunities across new labs, instruments, geographies, sites, and use cases within existing accounts

● Manage the full sales cycle from discovery through contracting, using modern sales methodologies (MEDDIC, MEDDPIC, Force Management, or similar)

● Maintain a rigorous, accurate pipeline with consistent forecasting and visibility to leadership

● Build and expand relationships across the customer organization, from individual contributors to executive sponsors

● Identify and close expansion opportunities across new labs, instruments, geographies, sites, and use cases within existing accounts

● Partner with the Delivery Manager to ensure smooth handoff from sales to delivery, maintaining continuity of scientific context

Market & Thought Leadership

● Represent TetraScience at industry conferences, seminars, and customer events as a scientifically credible voice

● Contribute customer and market insights back to product, marketing, and science teams to inform roadmap and messaging

● Help develop compelling content — case studies, solution briefs, demo narratives — that advances the category

Requirements

What You Bring

● Advanced degree in a life science, chemistry, or engineering discipline preferred MS or PhD); equivalent practical experience considered

● 7+ 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

Benefits

  • Competitive Salary and equity in a fast-growing company.
  • Supportive, team-oriented culture of continuous improvement.
  • Generous paid time off (PTO).
  • Flexible working arrangements - Remote work.

We are not currently providing visa sponsorship for this position

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What this application asks

workable

First name, Last name, Email, Headline, Phone, Address, Education, Experience, Summary, Resume, Cover letter

  • Do you have a scientific background in academics? yes / no
  • Do you have 5+ years professional experience in Life Sciences? yes / no
  • Do you have 5+ years of technical architecture experience? yes / no
  • What do you see as the biggest pain points for pharma data management? written answer
  • Who do you think Tetra's competitors are? written answer
  • Project spotlight – end-to-end delivery Describe a project where you delivered a technical solution for scientific users. State the scientific workflow outcome you aimed to enable, list the main systems or data sources you integrated, and highlight one design decision that made the biggest difference to the result. written answer
  • When a tech roll-out failed Tell us about a technology you (or a team you worked with) introduced that scientists ultimately rejected. Explain the need the tool was meant to address, give two specific reasons adoption failed, and outline one different tactic you would try if you could start over. written answer
  • Tough stakeholder moment Write about your most challenging interaction with a customer or internal stakeholder. Summarize the situation and the competing interests, explain two concrete actions you took to resolve it, and state one lesson you now apply elsewhere. written answer
  • Rapid prototyping tools List up to three tools or frameworks you have adopted in the last 18 months to test ideas or build MVPs quickly. For each, give a one-sentence example of how it sped up decision-making. written answer
  • Biggest data-modeling challenge Describe the most daunting data-modeling problem you have faced. Explain why it was difficult, highlight the hardest technical hurdle and the hardest scientist-workflow hurdle, and note the key lesson you learned that you now reuse on other projects. written answer
  • Advocate for a solution Describe two situations where you have to convince and evangelize to scientists to adopt your solution and convince technical audience to not build solutions themselves. For each, give specific examples on what has worked and what has not (what you would do more vs would do less next time). written answer
  • Start up Provide concrete examples of you fitting and thriving in a fast-pace, high urgency, start up environment. written answer

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