[Remote] Scientific Data Architect - New York, NY at TetraScience

New York, New York, United States

TetraScience Logo
Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Research, Biotechnology, AIIndustries

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
  • Ability to thrive in collaborative environments with scientists, product managers, and engineers
  • Rich experience applying cutting-edge data methodologies to the biopharma R&D domain
  • Insatiable learner with a track record of deeply learning new tools, methods, and domains
  • Embodies principles of extreme ownership with a demonstrated history of building extensible data models and applications for Biopharma end users

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 and solutions (inferred from role title and context)

Skills

Scientific Data Architecture
AI
Data Management
Cloud Infrastructure
Prototyping
Scientific Computing

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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