Scientific Data Architect - United Kingdom

London Source: WhatJobs

£80,000–£100,000

Scientific Data Architect - United Kingdom

Who We Are

TetraScience is the Scientific Data and AI Cloud company, catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets, which we bring to life in a growing suite of next‑gen lab data management solutions, scientific use cases, and AI‑enabled outcomes.

Who You Are

You are a product‑minded, outcome‑obsessed driver of technical scientific solutions, a high‑velocity self‑starter who refuses to let uncertainty obstruct your path. You roll up your sleeves, prototype, demo, and build to accelerate delivery, collaborate with scientists, product managers, and engineers, and transform complex scientific data into actionable outcomes. You bring rich experience applying cutting‑edge data methodologies to the biopharma R&D domain, are an insatiable learner, and embody extreme ownership, having built extensible data models and applications for Biopharma end users.

What You Have Done

PhD with 7+ years / Masters with 10+ years of industry experience in life sciences with extensive domain knowledge in drug discovery, preclinical development, CMC, 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 excellent communication and storytelling abilities
Advised scientists in a consulting capacity to further research, development, and quality testing outcomes

Requirements

Strong programming skills in Python and data modeling (tabular & JSON)
Experience with lab software integration (ELN/LIMS) via APIs
Knowledge of scientific data pipelines and instrument output file formats
Ability to design and implement data visualizations and application frameworks (e.g., Streamlit, Plotly, holoviews)
Experience in collaborating with Scientific Business Analysts, customer scientists and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid)
Rapid learning of new technologies, such as AWS services or scientific analysis applications

What You Will Do

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 integration via APIsData visualization and app development in Python (app frameworks like Streamlit, Plotly, holoviews)
Collaborate with SBAs, customer scientists, and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid)
Programmatically interrogate 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 the Tetra Data Platform
Rapidly learn new technologies (e.g., new AWS services or scientific analysis applications) to develop and troubleshoot use cases