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 or a Master's degree with 10+ years of industry experience in life sciences, including extensive domain knowledge in 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, along with experience collaborating with cross-functional teams and engaging diverse audiences. Candidates must also demonstrate extreme ownership and a history of building extensible data models and applications for Biopharma end users.

Responsibilities

The Scientific Data Architect will be a critical team member in industrializing Scientific AI, 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 performing extensive exploratory data analysis and workflow optimization to enable scientific outcomes, advising scientists in a consulting capacity, and leveraging excellent communication and storytelling abilities to engage diverse audiences from scientists to executive stakeholders.

Skills

Data Architecture

Scientific Data

Cloud

Data Management

Prototyping

Product Development

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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