Full-Time

Senior Scientific Data Engineer

TetraScience

TetraScience

201-500 employees

Cloud-native platform centralizing scientific data

Compensation Overview

$140k - $200k/yr

No H1B Sponsorship

Cambridge, MA, USA

Hybrid

Hybrid work in Cambridge, Massachusetts.

Category
Data & Analytics (1)
Required Skills
LLM
Streamlit
Agile
Python
React.js
Jupyter
Software Testing
Data Visualization
SQL
Data Engineering

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Requirements
  • At least 8 years of experience building data products as a Data Engineer or in a similar field.
  • At least 8 years of experience working in Python and SQL with a focus on data.
  • Experience leading projects, managing requirements, and handling timelines.
  • Experience managing multiple customer-focused implementation projects across cross-functional teams, building sustainable processes, and managing delivery milestones.
  • Excellent communication skills, attention to detail, and confidence in taking control of project delivery.
  • Ability to quickly understand a highly technical product and effectively communicate with product management and engineering.
Responsibilities
  • Lead the Scientific Data Engineering team and help build Tetra Data and productizable solutions as 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 solutions based on consensus.
  • Own the construction of data models, prototypes, and integration solutions that drive customer success.
  • Use AI agents to build comprehensive data schemas and parsers for pre-clinical data from R&D lab instruments, manufacturing, contract research organizations, contract development and manufacturing organizations, electronic laboratory notebooks, and laboratory information management systems, using formats such as .xlsx, .pdf, .txt, .raw, .fid, and vendor binaries.
  • Extract reusable schema components and parsing functions and productize them into Python libraries.
  • Build high-quality data pipelines with full unit-test and integration-test coverage to produce high-fidelity data.
  • Build data applications, reports, and dashboards using React, Streamlit, Jupyter notebooks, and related tools.
  • Collaborate with product managers, project managers, business analysts, data architects, and machine learning engineers to deliver data products.
  • Verify that solutions fulfill customer requirements and provide value.
  • Serve as a quality gatekeeper by designing with quality backed by unit tests, integration tests, and utility functions.
  • Lead team-wide process and technology improvements focused on product quality and developer experience.
  • Rally the team to complete Agile Sprint commitments and identify and resolve team inefficiencies.
  • Resolve blockers and unclear requirements and drive project execution.
  • Provide mentorship to junior Scientific Data Engineers and demonstrate technical leadership.
  • Supervise and collaborate on project executions and deliver mission-critical implementations.
Desired Qualifications
  • Experience with data plotting and dashboarding tools such as React and/or Streamlit is strongly preferred.
  • Experience working with pre-clinical data and lab scientists is strongly preferred.

TetraScience provides a cloud-based platform that collects and centralizes data from various laboratory instruments and software used in biopharmaceutical research and manufacturing. The system works by harmonizing scattered data into a consistent format, making it easier for scientists to use information for artificial intelligence and machine learning applications. Unlike many competitors, this platform is vendor-neutral and open, meaning it can connect to any piece of lab equipment regardless of the manufacturer. The company’s goal is to improve scientific outcomes by automating data management, allowing researchers to process information in seconds rather than hours.

Company Size

201-500

Company Stage

Series B

Total Funding

$117.2M

Headquarters

Boston, Massachusetts

Founded

2019

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Simplify Jobs

Simplify's Take

What believers are saying

  • Syngenta selected Tetra OS on April 22, 2026 for industrial-scale crop R&D automation.
  • Takeda's October 2025 SAIL partnership creates repeatable Scientific AI templates for rollout.
  • Matt Studney joined in January 2026, bringing Merck credibility and enterprise transformation relationships.

What critics are saying

  • Thermo Fisher can bundle competing workflows and compress TetraScience margins by 2027.
  • Customer adoption hinges on expensive Sciborg implementation, slowing sales cycles and burning cash.
  • Benchling, Veeva, and LabWare own adjacent workflows, risking TetraScience becoming a feature, not a platform.

What makes TetraScience unique

  • Tetra OS unifies instruments, CROs, and AI-ready data across pharma R&D.
  • Bayer expanded TetraScience deployment in November 2025 across pharma and crop science.
  • Thermo Fisher collaboration in January 2026 validates TetraScience as an enterprise laboratory platform.

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Benefits

Unlimited PTO

100% company paid health, dental, & vision

Company paid life insurance

401k savings

Company paid disability insurance

Equity program

Flexible work arrangements

Growth & Insights and Company News

Headcount

6 month growth

3%

1 year growth

2%

2 year growth

0%
PR Newswire
Jan 15th, 2026
TetraScience Appoints Matt Studney as Chief Customer Officer, Signaling Industry Shift Toward Platform-Based Scientific AI

TetraScience appoints Matt Studney as Chief Customer Officer, signaling industry shift toward platform-based Scientific AI. News provided by. 24-Year Merck Veteran and Former SVP of R&D IT Joins TetraScience to Help Industrialize Scientific Data and AI Across Biopharma BOSTON, Jan. 15, 2026 /PRNewswire/ - TetraScience, the Scientific Data and AI company, today announced the appointment of Matt Studney as Chief Customer Officer. Studney is a seasoned business, R&D, and technology leader with more than two decades of experience operating at the intersection of science, data, and engineering. Most recently, Studney served as Senior Vice President of R&D IT and Key Partnerships at Merck, where he led large-scale modernization of scientific, laboratory, and development platforms and helped scale data, cloud, and AI capabilities across the full R&D continuum. His work enabled faster scientific decision-making, improved reproducibility, and more resilient digital foundations for over 18,000 scientists and researchers worldwide. Studney's decision to join TetraScience reflects a broader inflection point in the biopharma industry. As scientific complexity accelerates and AI becomes central to competitive advantage, platform-based approaches to scientific data and AI are increasingly replacing bespoke, project-driven solutions across discovery, development and manufacturing. "Matt has lived firsthand the limits of artisanal approaches to scientific data and AI," said Patrick Grady, Co-Founder and CEO of TetraScience. "His move to TetraScience signals that the center of gravity is shifting - from bespoke internal efforts toward shared platforms purpose-built to make scientific intelligence durable, cumulative, and scalable." "Matt is a world-class operational leader with unparalleled credibility and relationships within the pharmaceutical industry, and his appointment represents a safe and trusted choice for pharmaceutical companies looking to partner with TetraScience on their scientific data and AI transformation journeys," added Grady. At Merck, Studney designed, established and governed strategic partnerships with AWS, Accenture, Veeva, NVIDIA, BCG X, and QuantumBlack, while overseeing modernization across lab, clinical, and manufacturing technologies. His initiatives helped reduce discovery cycle times by 33%, accelerate regulatory submissions by up to four weeks, and deliver more than $100 million in savings within the first six months of a multi-year optimization program. "Over the course of my career in one of the world's most complex pharmaceutical organizations, I've seen firsthand what works - and what breaks - when you try to scale scientific intelligence inside global pharma," said Studney. "The AI era makes clear that true transformation now requires a fundamentally new architectural foundation. Scientific intelligence cannot scale on fragmented data or bespoke workflows. TetraScience has built the platform needed to industrialize scientific data and make learning cumulative across the enterprise. Patrick's long-standing vision for Scientific AI, combined with the company's deep technical and scientific capabilities, makes clear that TetraScience is the natural steward of this next phase of the industry." Studney is a recognized industry voice across global technology and biopharma leadership forums, advising organizations on AI enablement, platform strategy, and partnership governance. At TetraScience, he will partner closely with biopharma customers to help them move beyond project-by-project modernization toward a shared scientific data and AI platform, working side-by-side through the organizational and operational change this transition requires. Through TetraScience's Sciborg model, his mandate is to translate platform architecture into durable adoption and measurable scientific, operational, and economic outcomes across discovery, development, and manufacturing. About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. Tetra OS integrates the Scientific Data Foundry, Scientific Use Case Factory, Tetra AI, and Sciborgs into a single, AI-native platform. Together, these capabilities turn fragmented scientific data and workflows into governed, reusable, and compounding intelligence across discovery, development, and manufacturing. TetraScience is trusted by leading biopharma organizations and ecosystem partners including NVIDIA, Databricks, Snowflake, Google, and Microsoft. For more information, visit tetrascience.com.

Yahoo Finance
Aug 13th, 2025
TetraScience Launches Tetra Workflows to Automate Scientific Data Workflows at Scale

BOSTON, Aug. 13, 2025 /PRNewswire/ - TetraScience, the Scientific Data and AI Cloud company, today announced the launch of Tetra Workflows, a comprehensive solution that fundamentally transforms how laboratories manage and automate scientific data workflows at scale.

BioSpace
Jan 16th, 2025
TetraScience Collaborates with Microsoft To Advance Scientific AI at Scale

TetraScience collaborates with Microsoft to advance Scientific AI at scale.

HIT Consultant
Jan 16th, 2025
Tetrascience & Microsoft Partner To Advance Scientific Ai In Biopharma

What You Should Know: – TetraScience, a provider of scientific data cloud solutions announced a strategic collaboration with Microsoft to accelerate the adoption of artificial intelligence (AI) in the biopharmaceutical industry. – The strategic partnership combines TetraScience’s Scientific Data and AI Cloud with the power and security of Microsoft Azure, creating a robust platform for scientific organizations to extract valuable insights from their complex experimental data.Explosion of Scientific Data ChallengesThe biopharmaceutical industry is facing a critical challenge: the explosion of scientific data. While AI holds immense promise for accelerating drug discovery and development, much of this data remains trapped in proprietary formats and scattered across disparate systems. This hinders the effective training and deployment of AI models, limiting the potential for breakthroughs.Harmonizing Scientific Data and Empowering AI WorkflowsThe TetraScience and Microsoft collaboration addresses this challenge head-on. By providing a comprehensive solution that encompasses massive computational power, advanced AI models, sophisticated scientific data ontologies, and deep scientific expertise, the partnership empowers organizations to overcome data silos and unlock the full potential of AI.TetraScience’s Scientific Data and AI Cloud is purpose-built to replatform and engineer scientific data into powerful data models and domain-specific use cases. This harmonizes data from hundreds of scientific instruments and vendor formats, ensuring that experimental context is preserved for multimodal analytics and AI model training.Microsoft Azure provides the enterprise-grade infrastructure and computational backbone for demanding scientific workloads, including real-time analytics and large-scale AI applications. This ensures that researchers have the resources they need to train and deploy sophisticated AI models.Preliminary Collaboration ResultsThis collaboration is already delivering tangible results

NVIDIA
Nov 13th, 2024
Japan Develops Next-Generation Drug Design, Healthcare Robotics and Digital Health Platforms

At AI Summit Japan, TetraScience, a company that engineers AI-native scientific datasets, announced a collaboration with NVIDIA to industrialize the production of scientific AI use cases to accelerate and improve workflows across the life sciences value chain.