Scientific Business Analyst - Synthetic Chemistry

1w1 week ago

TetraScience

Cambridge, US · Full-time · $180,000 – $240,000

About this role

TetraScience is the Scientific Data and AI Cloud company catalyzing the Scientific AI revolution with AI-native scientific data sets and next-gen lab data management solutions. As a Scientific Business Analyst, you bridge scientific insights and cutting-edge technology with deep domain knowledge in Synthetic Chemistry. You transform complex scientific data into actionable AI/ML outcomes for life sciences R&D and Quality personas.

You will investigate customer datasets to identify gaps and AI-readiness factors, perform exploratory data analysis, and define data transformations. Collaborate with scientists to define and refine AI/ML-driven use cases, while documenting workflows and ontologies. Engage stakeholders through interviews, demonstrations, and strategic recommendations to drive data value.

Thrive collaborating with scientists, product managers, and engineers in a high clock speed environment. Embody extreme ownership, self-discipline, and the principles in the Tetra Way letter from our CEO. Review it carefully to ensure alignment with our unique company and team building approach.

Join the category leader partnering with top compute, cloud, data, and AI infrastructure players. Forge a new category that will forever change the life sciences industry through innovative data enrichment and AI applications. Maximize scientific data value with forward-thinking determination.

Requirements

PhD with 15+ years of industry experience in life sciences
Extensive domain knowledge in Small Molecule Process Chemistry and Synthetic Chemistry
Strategic, analytically minded professional bridging scientific insights and technology
Skilled at uncovering innovative use cases that drive AI and machine learning applications
High clock speed and forward-thinking individual developing requirements for complex R&D solutions
Demonstrated history of deriving maximum value from data through enrichment, analysis, and AI integration
Embody principles of extreme ownership
Extreme self-discipline and determination

Responsibilities

Investigate customer datasets to identify gaps, enrichment opportunities, and AI-readiness factors
Collaborate with customers to define, iterate, and refine AI/ML-driven scientific use cases
Interview scientists and guide them in expanding and leveraging their data for AI applications
Perform exploratory data analysis (EDA) and define data transformations for AI/ML use cases
Develop workflow diagrams, process mappings, AS-IS/TO-BE workflows, and ontology definitions
Provide feedback on AI/ML models to enhance scientific outcomes and improve product offerings
Conduct technical demonstrations, showcase AI applications, and drive adoption
Proactively suggest experiments or data strategies that strengthen customer insights and outcomes