Scientific Business Analyst, DMPK / Metabolite ID at TetraScience

Cambridge, Massachusetts, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Biotechnology, Pharmaceuticals, Life SciencesIndustries

Requirements

PhD with 15+ years of industry experience in life sciences
Extensive domain knowledge in DMPK / Metabolite ID including ADME (Absorption, Distribution, Metabolism, Excretion)
PK/PD Modeling (NONMEM, Phoenix WinNonlin)
In vitro / In vivo Studies (microsomes, hepatocytes, animal models)
Bioanalytical LC-MS/MS
CYP450 Enzyme Profiling & Metabolite Identification
Proven track record of defining and

Responsibilities

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: Develop workflow diagrams, process mappings, AS-IS/TO-BE workflows, and ontology definitions
AI Model Evaluation: Provide feedback on AI/ML models to enhance scientific outcomes and improve product offerings
Customer Education and Demonstration: Conduct technical demonstrations, showcase AI applications, and drive adoption
Strategic Recommendations: Proactively suggest experiments or data strategies that strengthen customer insights and outcomes

Skills

Key technologies and capabilities for this role

DMPKMetabolite IDAIMachine LearningScientific Data ManagementData AnalyticsBusiness Analysis

Questions & Answers

Common questions about this position

Is this role remote or on-site?

This is an on-site position.

What domain knowledge is required for this role?

Deep domain knowledge in DMPK and Metabolite ID is required.

What key skills and traits are needed to succeed in this position?

Candidates need to be strategic and analytically minded, with high clock speed, forward-thinking, extreme ownership, self-discipline, and determination. Proficiency in data analysis, enrichment, and integration with AI/ML is essential.

What is the company culture like at TetraScience?

TetraScience emphasizes a unique values and ethos outlined in 'The Tetra Way' letter by the CEO, which candidates must review and embody daily. The culture focuses on catalyzing the Scientific AI revolution through collaboration and innovation in life sciences.

What makes a strong candidate for this Scientific Business Analyst role?

Strong candidates have deep DMPK and Metabolite ID expertise, passion for bridging science and technology, experience deriving value from data via AI/ML, and embody extreme ownership, self-discipline, and the principles in The Tetra Way.

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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