Scientific Product Marketing Manager - Scientific AI Use Cases

United States

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Not SpecifiedCompensation

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

Full TimeJob Type

UnknownVisa

Scientific Data, AI, Biotechnology, PharmaceuticalsIndustries

Requirements

The ideal candidate is an elite product marketing leader with a deep understanding of the scientific lifecycle, biopharma needs, and AI deployment challenges. They must be a high clock-speed thinker, a doer, a collaborator, and an evangelist, passionate about data and AI in science. A demonstrated history of delivering best-in-class products to market and ensuring high customer adoption, embodying extreme ownership, is essential. Experience in the digitalization of the life sciences laboratory and a rejection of the status quo in data management are also key.

Responsibilities

The Scientific Product Marketing Manager will own the product marketing strategy and execution for Scientific Analytics and AI use cases. This includes defining and refining messaging and positioning, developing packaging, pricing, and tiering strategies, and creating marketing content such as solution briefs, blog posts, webinars, and white papers. They will also partner with sales and field enablement to deliver effective tools and resources to drive awareness, education, and pipeline for Scientific AI solutions.

Skills

Product Marketing

Go-to-market Strategy

Scientific Data

Drug Discovery

Data Management

Data Visualization

Biopharma

Messaging

Content Strategy

Storytelling

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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