Senior UX Designer, Scientific AI at TetraScience

Boston, Massachusetts, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Scientific AI, Pharmaceutical, BiotechnologyIndustries

Requirements

6+ years of UX design experience, with 1+ years leading AI/ML-powered enterprise platforms in life sciences, healthcare, or regulated environments
Portfolio demonstrating end-to-end ownership of scientific interfaces including complex data visualization, AI interface design, and workflow optimization for non-technical users
Proven ability to influence product strategy by translating scientific workflows into AI interaction patterns (e.g., multi-model comparisons, iterative retraining interfaces)
Experience collaborating with scientists or AI teams to design interfaces that expose model inputs/outputs, uncertainty metrics, and feedback mechanisms
Familiarity with life sciences workflows (e.g., assay development, computational biology) and regulated environments (e.g. GxP)
Proficiency in Figma, Miro, or similar tools for rapid prototyping
Strong Communicator. You communicate clearly and persuasively in multiple mediums with product managers, engineers, stakeholders, and customers
This role follows a hybrid work model, with an expectation of being onsite at the client’s office 2–3 days per week

Responsibilities

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 (60-80% hands-on)
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

Skills

UX Design

Wireframes

Prototypes

High-Fidelity Interfaces

AI Workflows

User Research

Scientific Data

ELN

LIMS

Product Roadmaps

TetraScience

Cloud platform for scientific data management

About TetraScience

TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.

Boston, MassachusettsHeadquarters

2019Year Founded

$113.8MTotal Funding

SERIES_BCompany Stage

AI & Machine Learning, Biotechnology, HealthcareIndustries

51-200Employees

Benefits

Unlimited PTO

100% company paid health, dental, & vision

Company paid life insurance

401k savings

Company paid disability insurance

Equity program

Flexible work arrangements

Risks

Rapid AI development may outpace TetraScience's integration capabilities, risking obsolescence.

Dependency on partners like Google Cloud and NVIDIA could pose risks if disrupted.

International expansion may expose TetraScience to regulatory and compliance challenges.

Differentiation

TetraScience offers a vendor-neutral, open, cloud-native platform for scientific data management.

The platform integrates with any lab equipment or software, enhancing flexibility and adaptability.

TetraScience's Scientific Data Cloud centralizes and harmonizes data, preparing it for AI/ML applications.

Upsides

Partnerships with NVIDIA and Google Cloud enhance AI-native scientific datasets and capabilities.

Collaboration with Databricks accelerates the Scientific AI revolution in life sciences.

Bayer AG partnership maximizes scientific data value, driving innovation in biopharma.

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