Full-Time

Scientific Business Analyst-Boston or Bay Area

Posted on 11/7/2025

TetraScience

TetraScience

201-500 employees

Cloud-native platform centralizing scientific data

No salary listed

Boston, MA, USA + 1 more

More locations: California, USA

Hybrid

Onsite 4-5 days/week in Boston or Bay Area; remote options only when not at customer sites.

Category
Business & Strategy (2)
,
Required Skills
Machine Learning
Data Analysis
Requirements
  • PhD with 15+ years of industry experience in life sciences, preferably across pharma, biotech, or health tech, with deep domain expertise in discovery, preclinical, CMC, and/or Quality.
  • Extensive hands-on experience or direct oversight in high throughput screening, preclinical toxicology, materials engineering, analytical development, drug substance synthesis and manufacturing.
  • Delivered requirements for AI/ML-driven solutions in operational or productized environments that improved efficiency, reduced cost, and enhanced data utilization.
  • Exceptional communication and storytelling ability to engage technical and executive stakeholders.
  • Prior experience in customer-facing, consulting, or commercial-scientific interface roles.
Responsibilities
  • You will be a critical team member in a unique partnership to industrialize Scientific AI. As such, you will engage directly with customers onsite up to 4-5 days per week in the Boston or Bay Area Region.
  • 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.

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

Simplify Jobs

Simplify's Take

What believers are saying

  • Matt Studney's appointment brings $100M+ pharma ROI track record and 24-year Merck credibility.[Recent News]
  • Tetra Workflows expansion into automation orchestration captures workflow gap competitors cannot address.[Recent News]
  • Bayer multi-division partnership validates platform scalability across heterogeneous scientific domains beyond pharma.[Recent News]

What critics are saying

  • Benchling captures 30% more biopharma adoption with faster deployment and lower costs.[Recent News]
  • IDBS E-WorkBook dominates 40% of top-20 pharmas via Danaher's established sales channels.[Recent News]
  • Open-source scientific schemas commoditize data standardization, enabling 70% in-house platform replacement.[Recent News]

What makes TetraScience unique

  • Only AI-native platform purpose-built for scientific data across discovery, development, manufacturing.[1][4]
  • Largest integrated partner ecosystem connecting 10+ top-20 pharma companies via vendor-neutral architecture.[4]
  • Sciborg model operationalizes adoption through dedicated change management and measurable ROI delivery.[Recent News]

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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

0%

1 year growth

-5%

2 year growth

-6%
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.

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