Adaptyv
Head of QC & Analytics(m/w/x)
Full-timeOn-siteSenior
Lausanne
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ADAdaptyv
Data Scientist, Lab & Protein Data(m/w/x)
Lausanne
Full-timeOn-siteExperienced
AI/ML
Data Science
Nejo AI Summary
Building data science layer for AI-driven biology experiments. Owning messy experimental data end-to-end required. Automated checks for data quality and anomaly detection.
Requirements
- Strong data science/bioinformatics background
- Python fluency (pandas, numpy, scientific stack)
- Owning messy experimental data end to end
- Biology grounding (proteins, assays, sequence/structure/function)
- Understanding data meaning, not just processing
- Statistical maturity
- Process control, anomaly detection, variability/batch effects handling
- Distinguishing drift from noise
- Prolific builder with shipped products
- Shipped pipelines, tools, models, datasets
- Concrete built products in real use
- Fast-paced work ethic
- Systematizing what works
- AI-native builder
- Default use of coding agents (e.g., Claude Code)
- Sharp judgment on AI-generated code
- Interdisciplinary work instinct
- Working across lab bench, software, and ML
- Treating automation and data infrastructure as part of job
- Experience with protein/sequence-structure data
- Experience with bioinformatics tooling
- Experience with structural data
- Experience with ML on experimental data
- Experience building datasets for model training/benchmarking
Tasks
- Build data science layer for Adaptyv's foundry
- Transform raw experimental readouts into clean, structured data
- Ensure data quality for binding, developability, biophysical, and functional assays
- Define criteria for good data for each assay type
- Create automated checks for data quality and anomaly detection
- Develop QC models to identify and correct bad data
- Collaborate with software and ML teams on data pipeline improvements
- Specify requirements for data flagging, rejection, and human review
- Link experimental results to protein sequence, structure, and design
- Generate high-quality, benchmarkable datasets from foundry output
- Apply statistical rigor to multi-condition data at scale
- Ensure results are interpretable and comparable across experiments
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Native
Tools & Technologies
- Python
- pandas
- numpy
- Claude Code
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Adaptyv and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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ADAdaptyv
Data Scientist, Lab & Protein Data(m/w/x)
Lausanne
Full-timeOn-siteExperienced
AI/ML
Data Science
Nejo AI Summary
Building data science layer for AI-driven biology experiments. Owning messy experimental data end-to-end required. Automated checks for data quality and anomaly detection.
Requirements
- Strong data science/bioinformatics background
- Python fluency (pandas, numpy, scientific stack)
- Owning messy experimental data end to end
- Biology grounding (proteins, assays, sequence/structure/function)
- Understanding data meaning, not just processing
- Statistical maturity
- Process control, anomaly detection, variability/batch effects handling
- Distinguishing drift from noise
- Prolific builder with shipped products
- Shipped pipelines, tools, models, datasets
- Concrete built products in real use
- Fast-paced work ethic
- Systematizing what works
- AI-native builder
- Default use of coding agents (e.g., Claude Code)
- Sharp judgment on AI-generated code
- Interdisciplinary work instinct
- Working across lab bench, software, and ML
- Treating automation and data infrastructure as part of job
- Experience with protein/sequence-structure data
- Experience with bioinformatics tooling
- Experience with structural data
- Experience with ML on experimental data
- Experience building datasets for model training/benchmarking
Tasks
- Build data science layer for Adaptyv's foundry
- Transform raw experimental readouts into clean, structured data
- Ensure data quality for binding, developability, biophysical, and functional assays
- Define criteria for good data for each assay type
- Create automated checks for data quality and anomaly detection
- Develop QC models to identify and correct bad data
- Collaborate with software and ML teams on data pipeline improvements
- Specify requirements for data flagging, rejection, and human review
- Link experimental results to protein sequence, structure, and design
- Generate high-quality, benchmarkable datasets from foundry output
- Apply statistical rigor to multi-condition data at scale
- Ensure results are interpretable and comparable across experiments
Work Experience
- approx. 1 - 4 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Native
Tools & Technologies
- Python
- pandas
- numpy
- Claude Code
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Adaptyv and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Adaptyv
Industry
Other
Description
The company builds advanced molecular biology workflows, assay automation, and software infrastructure for protein design.
Not a perfect match?
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