[Remote] Senior Product Manager - Enterprise Platform Administration at TetraScience

United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Biopharma, Life SciencesIndustries

Requirements

Strategic leadership and technical depth in cloud-based data platforms
Experience supporting cloud-based data platforms and driving initiatives to improve system reliability, security, and data accessibility
Ability to engage with customer technology leaders, understand their evolving needs, and deliver solutions that scale across multiple enterprise SaaS environments
Alignment with TetraScience values as outlined in "The Tetra Way" letter

Responsibilities

Develop scalable and compliant data infrastructure for biopharma enterprises to manage and analyze scientific data via data retrieval, advanced analytics, AI, and ML
Enhance platform administration capabilities for seamless data access, governance, and operational insights across vast scientific datasets
Define, release, and improve key platform capabilities such as identity and access management, data governance, operational analytics, and ML/AI infrastructure
Work directly with Scientific IT customers to ensure the product operates effectively with enterprise cloud environments and lab ecosystems, enabling visibility into PB-scale data and billions of scientific records
Collaborate with TetraScience engineering, architecture, data engineers, and customer teams to align platform administration with needs in data/metadata governance, access control, auditability, and ML/AI Ops
Drive initiatives to enhance system reliability, identity management, and permission frameworks for efficient data management, tracking, and analysis
Own the Enterprise Platform Administration product strategy and roadmap, prioritizing data governance, compliance, and operational intelligence
Define and optimize access management, authentication, and audit capabilities in alignment with regulatory requirements
Build relationships with Scientific Technology (IT) customers, understand their processes and objectives, introduce innovative ways to improve productivity, and solicit feedback
Research industry comparables and market trends to propose roadmap trade-offs between parity and innovation
Bring creative ideas and proposals to drive product improvements

Skills

Product Management

Data Governance

Identity and Access Management

Machine Learning

Advanced Analytics

Data Infrastructure

Scientific Data Management

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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