Dein persönlicher KI-Karriere-Agent
Scientific Data Architect(m/w/x)
Designing and implementing extensible data models for AI-native scientific data sets in life sciences. PhD with 4+ years or Masters with 8+ years industry experience required. Flexible remote work when not onsite with customers.
Anforderungen
- PhD with 4+ years or Masters with 8+ years industry experience in life sciences
- Extensive domain knowledge in drug discovery
- Extensive domain knowledge in preclinical development
- Extensive domain knowledge in CMC
- Extensive domain knowledge in product quality testing
- Proven track record defining AI/ML use cases
- Proven track record designing AI/ML use cases
- Proven track record prototyping AI/ML use cases
- Proven track record implementing AI/ML use cases
- Experience with cloud environments for AI/ML
- Collaboration with product managers
- Collaboration with software engineers
- Collaboration with scientific stakeholders
- Extensive exploratory data analysis
- Workflow optimization for scientific outcomes
- Engaging diverse audiences
- Excellent communication abilities
- Excellent storytelling abilities
- Advising scientists in consulting capacity
- Critical team member in Scientific AI industrialization
- Direct customer engagement onsite
- Understanding customer scientific data challenges
- Understanding customer requirements
- Accelerating solutions for customers
- Business proficiency of German (C1 level)
Aufgaben
- Engage directly with customers onsite
- Build strong customer relationships
- Understand scientific data challenges and requirements
- Accelerate customer solutions
- Design and implement extensible data models
- Design and implement reusable data models
- Capture scientific data efficiently
- Organize scientific data efficiently
- Ensure data model scalability
- Ensure data model future adaptability
- Translate scientific data workflows into solutions
- Leverage the Tetra Data Platform
- Own solution implementation
- Scope solution implementation
- Prototype solution implementation
- Implement data model design (tabular & JSON)
- Develop Python-based parsers
- Integrate lab software via APIs
- Develop data visualizations in Python
- Develop apps in Python
- Collaborate to develop models (ML, AI, statistical, hybrid)
- Collaborate to deploy models (ML, AI, statistical, hybrid)
- Interrogate proprietary instrument output files programmatically
- Iterate with scientific end users
- Iterate with technical stakeholders
- Drive solution development
- Drive solution adoption
- Deliver regular demos to stakeholders
- Attend regular meetings with stakeholders
- Communicate implementation progress proactively
- Deliver demos to customer stakeholders
- Collaborate with the product team
- Understand customer pain points
- Learn new technologies rapidly
- Troubleshoot use cases
Berufserfahrung
- 4 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Deutsch – verhandlungssicher
Benefits
Flexibles Arbeiten
- Flexible working arrangements
- Remote work when not at customer sites
Mehr Urlaubstage
- Generous paid time off (PTO)
Lockere Unternehmenskultur
- Supportive, team-oriented culture
Sonstige Vorteile
- Continuous improvement culture
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Scientific Data Architect(m/w/x)
Designing and implementing extensible data models for AI-native scientific data sets in life sciences. PhD with 4+ years or Masters with 8+ years industry experience required. Flexible remote work when not onsite with customers.
Anforderungen
- PhD with 4+ years or Masters with 8+ years industry experience in life sciences
- Extensive domain knowledge in drug discovery
- Extensive domain knowledge in preclinical development
- Extensive domain knowledge in CMC
- Extensive domain knowledge in product quality testing
- Proven track record defining AI/ML use cases
- Proven track record designing AI/ML use cases
- Proven track record prototyping AI/ML use cases
- Proven track record implementing AI/ML use cases
- Experience with cloud environments for AI/ML
- Collaboration with product managers
- Collaboration with software engineers
- Collaboration with scientific stakeholders
- Extensive exploratory data analysis
- Workflow optimization for scientific outcomes
- Engaging diverse audiences
- Excellent communication abilities
- Excellent storytelling abilities
- Advising scientists in consulting capacity
- Critical team member in Scientific AI industrialization
- Direct customer engagement onsite
- Understanding customer scientific data challenges
- Understanding customer requirements
- Accelerating solutions for customers
- Business proficiency of German (C1 level)
Aufgaben
- Engage directly with customers onsite
- Build strong customer relationships
- Understand scientific data challenges and requirements
- Accelerate customer solutions
- Design and implement extensible data models
- Design and implement reusable data models
- Capture scientific data efficiently
- Organize scientific data efficiently
- Ensure data model scalability
- Ensure data model future adaptability
- Translate scientific data workflows into solutions
- Leverage the Tetra Data Platform
- Own solution implementation
- Scope solution implementation
- Prototype solution implementation
- Implement data model design (tabular & JSON)
- Develop Python-based parsers
- Integrate lab software via APIs
- Develop data visualizations in Python
- Develop apps in Python
- Collaborate to develop models (ML, AI, statistical, hybrid)
- Collaborate to deploy models (ML, AI, statistical, hybrid)
- Interrogate proprietary instrument output files programmatically
- Iterate with scientific end users
- Iterate with technical stakeholders
- Drive solution development
- Drive solution adoption
- Deliver regular demos to stakeholders
- Attend regular meetings with stakeholders
- Communicate implementation progress proactively
- Deliver demos to customer stakeholders
- Collaborate with the product team
- Understand customer pain points
- Learn new technologies rapidly
- Troubleshoot use cases
Berufserfahrung
- 4 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Deutsch – verhandlungssicher
Benefits
Flexibles Arbeiten
- Flexible working arrangements
- Remote work when not at customer sites
Mehr Urlaubstage
- Generous paid time off (PTO)
Lockere Unternehmenskultur
- Supportive, team-oriented culture
Sonstige Vorteile
- Continuous improvement culture
Über das Unternehmen
TetraScience
Branche
Science
Beschreibung
TetraScience is the Scientific Data and AI company, catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets for lab data management solutions and AI-enabled outcomes.
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