Head of QC & Analytics (Biotech)

TL;DR

Head of QC & Analytics (Biotech): Own end-to-end quality control for protein assays and data integrity in an automated AI-driven wet lab with an accent on defining QC metrics, standards, and automated pipelines. Focus on scaling analytical readouts across thousands of samples, investigating failures, and collaborating with software teams to embed scientific logic into data processing and anomaly detection.

Location: Lausanne

Company

Building an automated lab that enables AI agents to run biology experiments, powering wet lab workflows for biopharmas, AI labs, and techbio startups with software-hardware integration and full observability.

What you will do

• Own QC for protein assays including binding (BLI/SPR), developability, and biophysical characterization across high-throughput experiments.
• Define acceptance criteria, SOPs, and quality checkpoints integrated into automated workflows.
• Lead investigations of assay failures and deviations, partnering with scientists for method validation.
• Specify and improve data processing pipelines for instrument outputs, defining good data criteria and QC rules.
• Apply statistical reasoning to data quality, anomaly detection, and pipeline reviews with software team.
• Automate manual QC bottlenecks and select laboratory informatics tools for scale.

Requirements

• B.Sc., M.Sc., or Ph.D. in Biochemistry, Analytical Chemistry, Biophysics, Bioengineering, or related field.
• 6+ years in protein science, analytical development, or QC, ideally high-throughput or CRO.
• Deep hands-on with protein binding assays (BLI/SPR): development, troubleshooting, data interpretation.
• Familiarity with developability and biophysical assays data challenges.
• Strong Python and/or R for data processing, QC automation, pipelines.
• Experience managing large datasets and building QC frameworks/SOPs in production environments.

Nice to have

• Startup, CRO, or high-throughput foundry experience.
• Familiarity with instrument data formats/APIs (Sartorius Octet, Cytiva Biacore).
• Statistical process control or quality methodologies for analytical data.
• Exposure to AI/ML-driven protein design workflows.
• Experience with LIMS, ELN, and data pipeline tooling.

Culture & Benefits

• Rapidly growing team scaling AI-driven wet lab experimentation.
• Hands-on senior leadership in mission-critical quality and data systems.
• Full-time onsite role in Lausanne.