[Remote] Scientific Data Architect - St Louis, US at TetraScience

St. Louis, Missouri, United States

Apply Now

Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Scientific Data, AI, Life SciencesIndustries

Requirements

PhD with 7+ years or Masters with 10+ years of industry experience in life sciences with 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, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments
Collaborated with cross-functional teams, including product managers, software engineers, and scientific stakeholders
Performed extensive exploratory data analysis and workflow optimization to enable scientific outcomes not previously possible
Engaged diverse audiences, from scientists to executive stakeholders using excellent communication and storytelling abilities
Advised scientists in a consulting capacity to further research, development, and quality testing outcomes
Product-minded, outcome-obsessed driver of technical scientific solutions
High velocity self-starter who refuses to let uncertainty obstruct path to designing and building solutions
Ability to prototype, demo, and build to accelerate delivery of products for end users
Thrives in collaborative environments with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes
Rich experience applying cutting-edge data methodologies to the biopharma R&D domain
Insatiable learner with track record of deeply learning new tools, methods, and domains
Embodies principles of extreme ownership with history of building extensible data models and applications for Biopharma end users
Extreme self-discipline and determination

Responsibilities

Engage directly with customers onsite a couple of days per week in the Copenhagen Region, building strong relationships, deeply understanding their scientific data challenges and requirements, and accelerating solutions
Design and implement extensible [data architectures/solutions] (inferred from role title and context)

Skills

Key technologies and capabilities for this role

Scientific Data ArchitectureAIData ManagementScientific Data PipelinesPrototypingScientific Computing

Questions & Answers

Common questions about this position

Is this position remote?

Yes, the position is remote.

What education and experience are required for this role?

Candidates need a PhD with 7+ years or a Masters with 10+ years of industry experience in life sciences, with extensive domain knowledge in drug discovery, preclinical development, CMC, or product quality testing.

What is the salary range for this position?

This information is not specified in the job description.

What is the company culture like at TetraScience?

TetraScience emphasizes values outlined in 'The Tetra Way' letter by the CEO, which candidates must review for fit; employees are expected to embody extreme ownership, high velocity self-starting, and collaboration with scientists, product managers, and engineers.

What makes a strong candidate for this Scientific Data Architect role?

Strong candidates are product-minded, outcome-obsessed self-starters with biopharma R&D experience, who prototype quickly, collaborate across teams, and demonstrate extreme ownership in building extensible data models for AI/ML integration.

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.

Land your dream remote job 3x faster with AI

Try Jobo Free