Bioptimus

Biology Data Quality Engineer

Bioptimus

full-time

Posted on:

Location Type: Remote

Location: France

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Tech Stack

Python

About the role

  • Develop and implement comprehensive data validation protocols for diverse biological datasets (histology, omics, clinical).
  • Establish and enforce data standardization practices to facilitate seamless integration and analysis across different data types.
  • Work closely with the R&D team to understand data requirements and address data quality concerns.
  • Maintain a detailed documentation of the data-quality assessment procedures, validation results, and data specifications.
  • Evaluate and validate external public data sources, ensuring they meet our quality standards.

Requirements

  • Omics Data Expertise. Deep understanding of transcriptomics data types (bulk, single-cell, spatial) and their specific quality considerations. Good knowledge of genomics and proteomics data.
  • Data Quality Management: Proven experience in implementing data quality control procedures and pipelines. Familiarity with data validation tools and techniques.
  • Analytical Skills: Strong analytical and problem-solving skills to identify and resolve data quality issues.
  • Programming & Data Analysis: Proficiency in Python, good knowledge of data visualization libraries (e.g. matplotlib).
  • Communication Skills: Excellent written and verbal communication skills to effectively convey data quality findings and recommendations.
  • Educational Background: MSc in Biology, Computational Biology, Bioinformatics.
Benefits
  • A collaborative and mission-driven work environment.
  • Competitive salary and equity package.
  • Flexible work arrangements, including remote options.
  • Opportunities for professional growth and leadership development.
  • Shape the future of biology and AI by contributing to groundbreaking work.
Applicant Tracking System Keywords

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

Hard Skills & Tools
data validation protocolsdata standardization practicesdata quality control proceduresdata validation toolsPythondata visualizationtranscriptomicsgenomicsproteomicsanalytical skills
Soft Skills
problem-solving skillscommunication skills