TetraScience

Scientific Business Analyst, Scientific AI

United States

Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Data, AI Cloud, Drug Discovery, Biotechnology, PharmaceuticalsIndustries

Job Description

Company: TetraScience

Location Type: Remote

Employment Type: [Not Specified] Salary: [Not Specified]

Position Overview

TetraScience is seeking a strategic, analytically minded professional with a passion for bridging scientific insights and cutting-edge technology. This role is crucial in catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets. You will collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes, driving AI and machine learning applications within the life sciences industry.

Who You Are

  • A strategic and analytical professional with a passion for science and technology.
  • Skilled at collaborating with scientists, product managers, and engineers.
  • Possess deep domain knowledge in drug discovery/preclinical development, CMC, or Quality.
  • Adept at uncovering innovative use cases that drive AI and machine learning applications.
  • Able to engage effectively with both scientists and business leaders.
  • High clock speed and forward-thinking individual.
  • Passionate about developing requirements for complex solutions targeted to R&D and Quality personas in Life Sciences.
  • Embodies the principles of extreme ownership.
  • Demonstrated history of deriving maximum value from data through enrichment, analysis, and integration with AI/ML applications.
  • Possesses extreme self-discipline and determination.

Requirements

What You Have Done:

  • PhD with 15+ years of industry experience in life sciences.
  • Extensive domain knowledge in drug discovery (target ID through lead optimization), preclinical development, CMC (all drug modalities), or product quality testing.
  • Proven track record of defining and implementing AI/ML-driven use cases in productized environments.
  • Experience collaborating with cross-functional teams, including product managers, software engineers, and scientific stakeholders.
  • Experience performing extensive exploratory data analysis and workflow optimization to enable scientific outcomes.
  • Excellent communication and storytelling abilities, with experience engaging diverse audiences from scientists to executive stakeholders.
  • Experience advising scientists in a consulting capacity to further research, development, and quality testing outcomes.

What You Will Do:

  • Customer Data Exploration: Investigate customer datasets to identify gaps, enrichment opportunities, and AI-readiness factors.
  • Scientific Use Case Development: Collaborate with customers to define, iterate, and refine AI/ML-driven scientific use cases.
  • Stakeholder Engagement: Interview scientists and guide them in expanding and leveraging their data for AI applications.
  • Data Analysis and Enrichment: Perform exploratory data analysis (EDA) and define data transformations for AI/ML use cases.
  • Workflow Documentation: Document workflows related to data analysis and AI/ML use case development.

Company Information

TetraScience is the Scientific Data and AI Cloud company, catalyzing the Scientific AI revolution. We are the category leader in this vital new market, generating more revenue than all other companies in the aggregate. In the last year alone, the world’s dominant players in compute, cloud, data, and AI infrastructure have converged on TetraScience as the de facto standard, entering into co-innovation and go-to-market partnerships.

Note: 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. It is impossible to overstate the importance of this document, and you are encouraged to take it literally and reflect on whether you are aligned with our unique approach to company and team building. If you join us, you will be expected to embody its contents each day.

Skills

Scientific Data
AI
Machine Learning
Drug Discovery
Preclinical Development
CMC
Quality
Data Analysis
Business Analysis
Product Management
Scientific Use Cases

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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