TetraScience

Data Engineer

• **What You Will Do**
• - Research data acquisition strategy for scientific lab instrumentation
• - Research and productionize file parsers for instrument output files (.xlsx, .pdf, .txt, .raw, .fid, many other vendor binaries)
• - Design and build data models and the corresponding data pipelines, unit tests, integration tests, and reusable utility functions
• - Cross-analyze instrument data with the same instrument type or scientific workflow to design common data model components.
• - Build visualization, report, and dashboards using Streamlit, Tableau, Jupyter notebook, etc.
• - Drive value for the customers - test and make sure the solution fulfills their requirements and provides value

Scientific Data Engineer

• 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 Copenhagen 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 (tabular & JSON)
• - Python-based parser development.
• - Lab software (e.g., ELN/LIMS) integration via APIs.
• - Data visualization and app development in Python (using app frameworks like Streamlit and plotting tools like holoviews and Plotly)
• Collaborate with Scientific Business Analysts (SBAs), customer scientists and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid)
• Programmatically interrogating proprietary instrument output files.
• Dynamically iterate 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 (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases

Scientific Data Architect

Technical Account Manager

• Providing a strategic technical partnership with Customers
• Bridge the gap between business objectives and technical execution
• Primary technical leader for scientific end-users
• Design, architect, and deliver impactful solutions to pharmaceutical and biotech customers
• Understand scientists' and R&D IT analysts' needs
• Analyze their data environment
• Assist in the design and implementation of solutions
• Enable customers to achieve faster ROI, reduced risk, smoother scaling, and accelerated product adoption
• Ensure long-term success of projects

Technical Account Manager, New York

• Providing a strategic technical partnership with Customers, bridging the gap between business objectives and technical execution.
• Primary technical leader for scientific end-users to design, architect, and deliver impactful solutions to pharmaceutical and biotech customers.
• Understand scientists' and R&D IT analysts' needs, analyze their data environment, assist in the design and implementation of our solutions.
• Enable customers to achieve faster ROI, reduced risk, smoother scaling, accelerated product adoption, and ensure the long-term success of projects.
• Drive adoption & success plan execution, conduct regular technical reviews, identify risks & recommend optimizations.
• Lead technical strategy for expansions, support POCs & co-innovation, and manage resolution for escalated issues.

Technical Account Manager – St Louis

• - Work with Product Managers and Solution Architects to understand business requirements, gather insight into potential positive outcomes, recommend potential outcomes, and build a solution based on consensus.
• - Take ownership of building data models, prototypes, and integration solutions that drive customer success.
• - Research and prototype data integration strategy for scientific lab instrumentation, prototype file parsers for instrument output files (.xlsx, .pdf, .txt, .raw, .fid, and many other vendor binaries).
• - Quality gatekeeper: design with quality backed by unit tests, integration tests, and utility functions.
• - Lead team-wide process/technology improvements on product quality and developer experience
• - Rally the team to finish Agile Sprint commitments. Actively surfacing team inefficiencies and striving to resolve them.
• - Driven by results. Have the pragmatic urgency to resolve blockers, unclear requirements, and make things happen.
• - Provide mentorship to junior SDEs and show leadership in every front

Senior Scientific Data Engineer

Product Designer

• Lead end-to-end UX design for AI-driven features, including wireframes, prototypes, and high-fidelity interfaces that integrate scientific data inputs (e.g., assays, instruments, ELN/LIMS) with AI model outputs.
• Collaborate with platform and science teams to translate algorithmic decision-making processes into intuitive user interactions.
• Partner with product managers and scientific stakeholders to define UX roadmaps that align with platform adoption goals.
• Advocate for user-centric design in AI product development, balancing technical feasibility with scientific user needs.
• Conduct lightweight user research directly with pharmaceutical clients to identify pain points in lab workflows.
• Rapidly prototype solutions and iterate based on stakeholder feedback, prioritizing high-impact improvements.

Senior UX Designer, Scientific AI

Security Engineer

• Own and evolve the organization’s entire application security posture, with a focus on application and cloud security across all product lines
• Perform offensive and defensive security assessments — threat modeling, code review, penetration testing, and vulnerability exploitation.
• Build and integrate automated security tooling (SAST, DAST, dependency scanning, IaC scanning) into CI/CD pipelines
• Develop security automation and internal tooling using Python, Bash, or Go.
• Partner with Engineering, DevOps, and Infrastructure teams to ensure secure AWS architectures (VPC, IAM, KMS, GuardDuty, CloudTrail, WAF).
• Oversee incident response and root cause analysis for product and infrastructure-level security events.
• Define and enforce secure coding standards, and lead threat modeling sessions for critical features and services
• Continuously hunt for vulnerabilities, test assumptions, and “break things safely” to strengthen the platform

Product Security Tech Lead

Business Analyst

• Customer Data Exploration: Investigate diverse customer datasets, identifying enrichment and AI-readiness opportunities.
• Scientific Use Case Development: Collaborate with customers to define, iterate, and implement innovative scientific AI/ML use cases.
• Stakeholder Engagement: Conduct onsite interviews and workshops to deeply understand customer challenges and data landscapes.
• Data Analysis and Enrichment: Perform exploratory data analysis and define transformation workflows that enable scientific AI.
• Workflow Documentation: Develop visual documentation including workflow diagrams, ERDs, and ontology definitions.
• AI Model Evaluation: Provide practical scientific input on model output, with suggestions to improve real-world performance.
• Customer Enablement: Deliver onsite demonstrations, conduct working sessions, and act as a trusted advisor in AI adoption.
• Strategic Insight: Propose new directions, experiments, or platforms that can amplify scientific discovery and development.

Scientific Business Analyst

• - You will be a Senior member of the Scientific Data Engineer team and helping build Tetra Data and productizable solutions, which is the foundation of the Data Engineering layer.
• - Work with Product Managers and Solution Architects to understand business requirements, gather insight into potential positive outcomes, recommend potential outcomes, and build a solution based on consensus.
• - Take ownership of building data models, prototypes, and integration solutions that drive customer success.
• - Research and prototype data integration strategy for scientific lab instrumentation, prototype file parsers for instrument output files (.xlsx, .pdf, .txt, .raw, .fid, and many other vendor binaries).
• - Quality gatekeeper: design with quality backed by unit tests, integration tests, and utility functions.
• - Lead team-wide process/technology improvements on product quality and developer experience.
• - Rally the team to finish Agile Sprint commitments. Actively surfacing team inefficiencies and striving to resolve them.
• - Driven by results. Have the pragmatic urgency to resolve blockers, unclear requirements, and make things happen.
• - Provide mentorship to junior SDEs and show leadership in every front.

• 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 (tabular & JSON)
• - Python-based parser development.
• - Lab software (e.g., ELN/LIMS) integration via APIs.
• - Data visualization and app development in Python (using app frameworks like Streamlit and plotting tools like holoviews and Plotly)
• Collaborate with Scientific Business Analysts (SBAs), customer scientists and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid)
• Programmatically interrogating proprietary instrument output files.
• Dynamically iterate 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 (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases

• - Providing a strategic technical partnership with Customers, you will bridge the gap between the business objectives and technical execution.
• - You will be the primary technical leader for scientific end-users to design, architect, and deliver highly impactful solutions to pharmaceutical and biotech customers.
• - You will work to understand scientists' and R&D IT analysts' needs, analyze their data environment, assist in the design and implementation of our solutions and enable customers to achieve faster ROI, reduced risk, smoother scaling, accelerated product adoption and ensure the long-term success of projects.
• - Primary technical point of contact across strategic accounts
• - Lifecycle engagement & adoption acceleration from presales to delivery
• - Technical health & risk management
• - Strategic planning and stakeholder management across sales, product management and engineering teams
• - Sales enablement & growth support
• - Deep and wide technical and science senior relationships
• - Provide proactive, prescriptive technical guidance
• - Act as a trusted advisor aligned to Customer outcomes
• - Drive adoption & success plan execution
• - Conduct regular technical reviews
• - Identify risks & recommend optimizations
• - Lead technical strategy for expansions
• - Support POCs & co-innovation
• - Manage resolution for escalated issues
• - Accelerate time to value
• - Improve stability & uptime
• - Strategic roadmap alignment
• - Prioritized support & faster resolutions
• - Higher ROI through continuous optimization
• - Support growth through hands on sessions and enablement presentations
• - Showcase tailored demonstrations to prospects, to both small and large audiences
• - Solution Mapping: Map business requirements to technical solutions.
• - ROI Calculation: Determine potential return on investment for proposed solutions.
• - Relationship Building: Cultivate relationships with clients, sales teams, and technical teams.
• - Working with the science and technology Partners such as Databricks and Google
• - Negotiation Skills: Collaborate with clients and sales teams to reach beneficial agreements.
• - Develop a deep understanding of the company's product or service offerings.
• - Design and showcase tailored demonstrations to prospects.
• - Contribute to RFPs/RFIs with detailed technical specifications and solutions
• - Ensure projects are kept on track and within scope.
• - Coordinate with various stakeholders to ensure the smooth flow of presales activities.

Technical Account Manager, TAM

QA Engineer

• Take ownership of the QA process and overall product quality.
• Review and use case requirement documents and technical design documents and provide timely and meaningful feedback.
• Understand application requirements and use-cases, create test cases, perform manual testing, track test runs and test cycles, report issues and track them meticulously.
• Independently estimate, prioritize, plan, and coordinate QE activities.
• Develop test cases that cover different edge cases based on use-cases, not let go of any details and be very nuanced in the QE approach.
• Use your quality engineering background to work seamlessly in a fast-paced environment while maintaining the strict quality process.
• Effectively collaborate with a diverse group of scientists, data engineers and application developers.
• Be driven by results - have a pragmatic approach and urgency towards evolving requirements, follow and resolve blockers and basically take things to resolution.
• Keep improving test coverage by continuously reviewing customer issues and usage patterns.
• Be curious about the science behind the application use-cases and be willing to continuously learn and adapt to the application.
• Utilize prior test automation experience to design and implement robust, effective workflow-based tests within our AI-based Playwright test framework.
• Use basic experience with databases and data verification to query and verify data integrity and correctness for scientific data applications.

Quality Engineer

• Investigate customer datasets to identify gaps, enrichment opportunities, and AI-readiness factors
• Collaborate with customers to define, iterate, and refine AI/ML-driven scientific use cases
• Interview scientists and guide them in expanding and leveraging their data for AI applications
• Perform exploratory data analysis (EDA) and define data transformations for AI/ML use cases
• Develop workflow diagrams, process mappings, AS-IS/TO-BE workflows, and ontology definitions
• Provide feedback on AI/ML models to enhance scientific outcomes and improve product offerings
• Conduct technical demonstrations, showcase AI applications, and drive adoption
• Proactively suggest experiments or data strategies that strengthen customer insights and outcomes

Scientific Business Analyst, DMPK, Metabolite ID

• 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 med chem teams on DMTA (design-make-test-analyze) cycles, ensuring scientific data flows between compound design, assay results, and decision-making workflows
• Map and harmonize scientific data across key platforms: LiveDesign (Schrödinger), D360, KNIME, internal databases (grdb) and other informatics tools; identify and resolve data comparability challenges across sites/vendors
• 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
• Work directly with partner’s scientists and TetraScience engineering teams to harmonize, contextualize, and enable advanced analytics on critical chemistry and DMPK datasets

Scientific Business Analyst, Medicinal Chemistry

Sales

• Develop and execute a comprehensive sales strategy to drive revenue growth and meet annual sales targets.
• Identify and pursue new business opportunities, expanding our customer base across the biopharma value chain.
• Stay up-to-date on industry trends and emerging technologies, positioning TetraScience as a thought leader in the market.
• Work closely with marketing and product teams to develop and implement go-to-market strategies and campaigns.
• Lead compelling presentations of TetraScience to a range of audiences from R&D IT, Informatics, Scientists and Data Scientists to Directors, VPs, CDOs and Digital Transformation Executives.
• Leverage and coordinate cross-functional teams, when necessary (Legal, Engineering, Marketing, Product), to efficiently navigate complex sales cycles.
• Aligning to the sales strategy, you will define and implement plans for the assigned accounts to achieve sales objectives.
• Maintain ongoing relationships with existing customers, ensuring high levels of customer satisfaction and retention.
• Manage sales forecasting and reporting and regularly update senior leadership on progress toward targets.
• Build and manage a high-performance sales team, setting clear targets and objectives to ensure individual and team success.
• You will coach your team to develop in their careers and inspire your team to do the best work of their life but will be completely comfortable inspecting and directing alongside coaching.
• Employ analytical skills and the ability to generate insights from data.

Head of Sales

Recruitment

Who We Are: TetraScience is the Scientific Data and AI Cloud 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.
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.
Who You Are: You are self-driven, highly organized, operate with urgency, and have a strong attention to detail. You enjoy coordinating, scheduling, and collaborating with candidates, recruiters, and external partners.
Responsibilities: Manage high-volume interview scheduling across multiple time zones, supporting a team of recruiters and numerous open requisitions in a fast-paced, high-growth startup environment
Applicant tracking system (ATS, Workable) organization & input, reporting, and process improvements
Coordinate and distribute NDAs and other candidate documentation in a timely manner, ensuring compliance and confidentiality
Draft and send offer letters, facilitating a smooth transition from candidate acceptance to onboarding
Partner closely with internal and external recruiters to streamline scheduling, candidate communications, and overall hiring operations
Act as the primary point of contact for candidates throughout the interview process, delivering a positive and professional candidate experience
Collaborate with hiring managers to align interview logistics, ensure readiness, and adjust quickly to changing priorities.
Help with onboarding of new employees
Monitor and maintain TetraScience's Career Site and LinkedIn job postings
Collaborate with recruiting team to understand hiring profile across markets and capabilities
Learn and execute our approach for identifying and hiring top performers
Contribute to continuous process improvement by identifying scheduling bottlenecks and implementing efficient solutions.

Recruiting Coordinator

Full-stack Engineer

• TetraScience is the Scientific Data and AI Cloud company catalyzing the Scientific AI revolution by designing AI-native scientific data sets and lab data management solutions.
• Company is category leader and collaborates with major compute, cloud, data, and AI infrastructure partners.
• Applicants should read the Tetra Way letter and align with the company’s values and ethos.
• Seeking a Senior .NET Engineer to design and develop high-performance, scalable applications using C#, .NET, and TypeScript; implement automated testing and GitHub Actions CI/CD; proficient in production debugging and AWS.

Scientific Data Engineer

Scientific Data Architect

Scientific Data Architect

Technical Account Manager, New York

Technical Account Manager – St Louis

Senior Scientific Data Engineer

Senior UX Designer, Scientific AI

Product Security Tech Lead

Scientific Business Analyst

Senior Scientific Data Engineer

Scientific Data Architect

Technical Account Manager, TAM

Quality Engineer

Scientific Business Analyst, DMPK, Metabolite ID

Scientific Business Analyst, Medicinal Chemistry

Head of Sales

Recruiting Coordinator

Senior Software Engineer, Agents