Scientific Data Architect

TetraScience

. Engage directly with customers onsite a couple of days per week in the Frankfurt Region, building relationships and understanding scientific data challenges and requirements.

Posted 9/18/2026full-timeBasel • SwitzerlandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing data models for scientific applications, with a strong focus on Python development, data visualization, and AI/ML-driven solutions. Possesses extensive knowledge in drug discovery and preclinical development, coupled with excellent communication skills for engaging diverse stakeholders.

Highest-signal resume keywords

Python Application DevelopmentData Model DesignAI/ML Use Case ImplementationLab Software Integration via APIsExploratory Data Analysis

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data VisualizationPython Parser DevelopmentJSON Data ModelingStatistical ModelingMachine LearningHybrid ModelingCloud Environment SolutionsWorkflow OptimizationScientific Data AnalysisProgrammatic Data Interrogation

Soft Skills

Excellent CommunicationStorytelling AbilitiesCollaborationCustomer EngagementConsulting Experience

Tools & Technologies

Tetra Data PlatformStreamlitHoloviewsPlotlyAWS Services

Industry Keywords

Life SciencesDrug DiscoveryPreclinical DevelopmentCMCProduct Quality Testing

Tech Stack

Tools & technologies

AWSCloudPython

About the role

Key responsibilities & impact

Engage directly with customers onsite a couple of days per week in the Frankfurt Region, building relationships and understanding scientific data challenges and requirements.
Design and implement extensible, reusable data models for scientific use cases.
Translate scientific data workflows into robust solutions leveraging the Tetra Data Platform.
Own, scope, prototype, and implement solutions involving data model design, Python parser development, lab software integration via APIs, data visualization, and Python application development.
Collaborate with Scientific Business Analysts, customer scientists, and applied AI engineers to develop and deploy models.
Iterate with scientific end users and technical stakeholders through regular demos and meetings to drive solution development and adoption.
Communicate implementation progress and deliver demos to customer stakeholders.
Collaborate with the product team to build and prioritize the roadmap based on customer pain points.
Learn new technologies and scientific analysis applications to develop and troubleshoot use cases.

Requirements

What you’ll need

PhD with +4 years or Masters with +8 years of industry experience in life sciences.
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.
Experience performing extensive exploratory data analysis and workflow optimization.
Excellent communication and storytelling abilities for diverse audiences, from scientists to executive stakeholders.
Experience advising scientists in a consulting capacity.
Experience designing data models, including tabular and JSON.
Python-based parser development.
Lab software integration via APIs, including ELN/LIMS.
Data visualization and app development in Python using frameworks such as Streamlit and tools such as holoviews and Plotly.
Experience developing and deploying ML, AI, mechanistic, statistical, and hybrid models.
Ability to programmatically interrogate proprietary instrument output files.
Ability to rapidly learn new technologies, such as AWS services and scientific analysis applications.
Business proficiency in German required (C1 level).
Must be willing to engage directly with customers onsite a couple of days per week in the Frankfurt Region.
Visa sponsorship is not currently provided for this position.

Benefits

Comp & perks

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