Scientific Data Architect - Frankfurt, Germany

Frankfurt, Hesse, Germany

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Scientific Data, AI, Cloud Computing, Data ManagementIndustries

Requirements

Candidates should possess a PhD with 7+ years of industry experience in life sciences, or a Master's degree with 10+ years of experience, focusing on drug discovery, preclinical development, CMC, or product quality testing. A proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments is essential. Experience collaborating with cross-functional teams, performing extensive exploratory data analysis, optimizing workflows, engaging diverse audiences, and advising scientists in a consulting capacity is also required. Deep domain knowledge in the biopharma R&D sector and a history of building extensible data models and applications for Biopharma end users are necessary.

Responsibilities

The Scientific Data Architect will be a critical team member industrializing Scientific AI by engaging directly with customers onsite a couple of days per week in the Frankfurt Region. Responsibilities include building strong customer relationships, deeply understanding their scientific data challenges and requirements, and accelerating solutions. The role involves transforming complex scientific data into actionable outcomes and maximizing the value of scientific data through analysis and integration with AI/ML.

Skills

Data Architecture

Scientific Data

Cloud

Data Management

Problem-Solving

Prototyping

Demoing

Collaboration

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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