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TetraScience is seeking a Scientific Data Architect to join their team in the Frankfurt region. You will be a critical member of a unique partnership to industrialize Scientific AI, working directly with customers onsite a couple of days per week in the Frankfurt Region to build strong relationships, deeply understand their scientific data challenges, and accelerate solutions.
In this role, you will design and implement extensible, reusable data models that efficiently capture and organize scientific data for scientific use cases, ensuring scalability and future adaptability. You will translate scientific data workflows into robust solutions leveraging the Tetra Data Platform. Your responsibilities include:
- Own, scope, prototype, and implement solutions including data model design (tabular & JSON), Python-based parser development, lab software (ELN/LIMS) integration via APIs, and data visualization/app development in Python using frameworks like Streamlit, holoviews, and Plotly
- Programmatically interrogate proprietary instrument output files
- Collaborate with Scientific Business Analysts, customer scientists, and applied AI engineers to develop and deploy models (ML, AI, mechanistic, statistical, hybrid)
- 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 the 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
TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. The company helps leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. Strategic partners include NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.
You are a product-minded, outcome-obsessed driver of technical scientific solutions with a high-velocity, self-starter mentality. You roll up your sleeves, prototype, demo, and build to accelerate delivery. You thrive collaborating with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes. You have rich experience applying cutting-edge data methodologies to the biopharma R&D domain, bridging understanding between present-day pain points and generalizable solutions. You are an insatiable learner with a demonstrated history of building extensible data models and applications for biopharma end users.
REQUIREMENTS:
- PhD with 4+ years OR Master's degree with 8+ 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
- Experience collaborating with cross-functional teams including product managers, software engineers, and scientific stakeholders
- Demonstrated extensive exploratory data analysis and workflow optimization to enable scientific outcomes not previously possible
- Excellent communication and storytelling abilities to engage diverse audiences from scientists to executive stakeholders
- Experience advising scientists in a consulting capacity to further research, development, and quality testing outcomes
- Business proficiency in German (C1 level) required
- No visa sponsorship available for this position
