Senior Assay and Data Specialist

Role Summary

Senior Assay and Data Specialist. You will work alongside wet lab assay scientists, automation engineers, and data scientists to build interconnected workflows, creating end-to-end data workflows for standardized cellular assays used for machine learning and AI initiatives. The role is both lab-based and computational, involving independent design, execution, interpretation of scientific experiments, and communication of findings as part of a multi-disciplinary project team.

Responsibilities

• Work in cross-functional teams to standardize and automate HT biochemical and cellular assays.
• Operate and optimize automated in-vitro assay workflows (mostly 2D, HT plate-based, flow-based).
• Ensure high-quality, high-throughput data capture, with well-structured metadata compliant with FAIR principles.
• Curate, process, and analyze large assay datasets, developing scripts/pipelines for QC and normalization.
• Collaborate with data engineers and data scientists to build predictive models (ML/AI) based on assay data.
• Continuously improve throughput and data integrity, driving automation and analytical maturity.

Assay Operations & Automation

• Develop, validate, and execute routine and complex in-vitro assays (cell-based, biochemical, flow-based, plate-reader, binding/functional).
• Perform troubleshooting and optimization of assay conditions to maximize reproducibility and throughput.
• Document all processes in ELN/LIMS, ensuring full traceability and metadata integrity.

Data Curation, QC, And Infrastructure Development

• Design and implement automated data ingestion and QC pipelines for assay outputs (plate-reader, HT flow, imaging, kinetic, etc.).
• Define and enforce data and metadata schemas for all assays.
• Build basic ETL (Extract–Transform–Load) pipelines into centralized storage (data lake or on-prem system).
• Liaise with informatics to connect instruments → LIMS/ELN → analytics layer.

Analytics & Modeling

• Perform statistical analysis and visualization (curve fitting, EC50/IC50, QC metrics, reproducibility analysis).
• Build and train machine learning models to predict assay behaviors, detect anomalies, or classify hits.
• Integrate multi-assay data (e.g., bioassay + biophysics + omics) into analytical frameworks for decision-making.
• Communicate data insights to program teams and leadership through dashboards or reports.

Qualifications

• PhD in Pharmacology, Bioengineering, Quantitative Biology, Computational Biology, or related field with 2 years of relevant experience
• Proven experience coding for data analysis and pipeline development
• Demonstrated understanding of assay design AND statistical interpretation
• Experience and in-depth technical knowledge of assay development with a dedication to quality and scientific rigor.
• Strong teammate with good communication skills and experience of working in multi-disciplinary teams.
• Ability to tackle challenges creatively, which contribute and improve assay technologies and processes.

Desirable Skills/Experience

• 3–6 years of experience in biopharma or biotech assay development/screening, ideally with automation exposure
• Experience working in antibody or small molecule discovery teams