Scientific Data Architect

October 20

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TetraScience

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Artificial Intelligence • Biotechnology • SaaS

TetraScience is a company dedicated to transforming raw scientific data into AI-native datasets for advanced scientific applications. By collaborating closely with leading biopharmaceutical companies, TetraScience enhances productivity, accelerates insights, and ensures data integrity across the scientific value chain. Their platform offers solutions for next-generation lab data management, AI-driven scientific outcomes, and compliance with industry standards. As the first company to provide a data and AI cloud built specifically for science, TetraScience enables its clients to liberate, unify, and transform their data, overcoming traditional data silos and boosting scientific productivity by providing a flexible, open, and collaborative infrastructure.

51 - 200 employees

Founded 2015

🤖 Artificial Intelligence

🧬 Biotechnology

☁️ SaaS

📋 Description

• Design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and future adaptability. • Translate scientific data workflows into robust solutions leveraging the Tetra Data Platform. • Own, scope, prototype, and implement solutions including: • - Data model design (tabular & JSON) • - Python-based parser development. • - Lab software (e.g., ELN/LIMS) integration via APIs. • - Data visualization and app development in Python (using app frameworks like Streamlit and plotting tools like holoviews and Plotly) • Collaborate with Scientific Business Analysts (SBAs), customer scientists and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid) • Programmatically interrogating proprietary instrument output files. • Dynamically iterate with scientific end users and technical stakeholders to rapidly drive solution development and adoption through regular demos and meetings • Proactively communicate implementation progress and deliver demos to customer stakeholders. • Collaborate with the product team to build and prioritize our roadmap by understanding customers’ pain points within and outside Tetra Data Platform. • Rapidly learn new technologies (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases

🎯 Requirements

• PhD with 7+ years / Masters with 10+ years of industry experience in life sciences with extensive domain knowledge in drug discovery (target ID through lead optimization), preclinical development, CMC (all drug modalities), or product quality testing. • Proven track record of defining, designing, prototyping, and implementing productized AI/ML-driven use cases in cloud environments • Collaborated with cross-functional teams, including product managers, software engineers, and scientific stakeholders. • Performed extensive exploratory data analysis and workflow optimization to enable scientific outcomes not previously possible. • Engaged diverse audiences, from scientists to executive stakeholders using your excellent communication and storytelling abilities. • Advised scientists in a consulting capacity to further research, development, and quality testing outcomes.

🏖️ Benefits

• Competitive Salary and equity in a fast-growing company. • Supportive, team-oriented culture of continuous improvement. • Generous paid time off (PTO). • Flexible working arrangements - Remote work when not at Customer Sites** • We are not currently providing visa sponsorship for this position.