AI Solutions Architect
OddballSalary not specified
Full Time
Expert & Leadership (9+ years)
Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Scientific Data, AI Cloud, Lab Data ManagementIndustries
Requirements
A PhD with 7+ years or a Master's degree with 10+ years of industry experience in life sciences is required, along with extensive domain knowledge in drug discovery, preclinical development, CMC, or product quality testing. Proven experience in defining, designing, prototyping, and implementing AI/ML-driven use cases in cloud environments is essential. Candidates must have a track record of collaborating with cross-functional teams, performing exploratory data analysis, optimizing workflows, engaging diverse audiences, and advising scientists. Strong communication and storytelling abilities are necessary.
Responsibilities
The Scientific Data Architect will be a critical team member in industrializing Scientific AI by engaging directly with customers onsite in the Basel Region a couple of days per week. Responsibilities include building strong customer relationships, deeply understanding their scientific data challenges and requirements, and accelerating solutions. The role involves designing, prototyping, and implementing productized AI/ML-driven use cases and optimizing workflows to enable scientific outcomes. The architect will also advise scientists in a consulting capacity to further research, development, and quality testing outcomes.
Skills
Data Architecture
Scientific Data
AI
Cloud
Data Management
Problem-Solving
Prototyping
Collaboration
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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