[Remote] Team Lead, Scientific Data Workflow Automation at TetraScience

Boston, Massachusetts, United States

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Scientific Data, AI Cloud, Lab Data ManagementIndustries

Requirements

Candidates must have 8+ years of experience in Python with a focus on data, and 3+ years of experience in Life Sciences or with scientific data. A minimum of 3 years of experience managing multiple simultaneous projects, leading and coordinating teams of engineers, and estimating complex software projects with accountability for delivery is required. Expertise in SQL, RDS, and associated technologies, along with excellent communication and technical writing skills, are essential. Experience with data plotting/dashboarding tools like Streamlit, Tableau, or Jupyter Notebook, and cloud infrastructure providers such as AWS, Azure, or GCP are considered a plus.

Responsibilities

The Team Lead, Scientific Data Workflow Automation will lead the team in automating lab workflows and unlocking the value of scientific data, guiding field development and product direction. They will coordinate forward-deployed engineers to rapidly deliver scientific workflow automation using Tetra products, and support pre-sales in designing and scoping technical projects. Responsibilities include running the agile development process, managing people and projects, identifying and clearing blockers, and driving successful delivery of complex client projects. The role also involves providing product feedback, making project improvements, self-starting in ambiguous situations, working with a geographically dispersed team, and mentoring engineers towards leadership and team capability growth.

Skills

workflow automation

data management

agile development

project management

team leadership

scientific data

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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