Bioinformatics Engineer

Insilico Medicine

Responsibilities:

• Develop and maintain data processing pipelines for diverse omics data types (bulk RNA-seq, proteomics, single-cell, epigenomics, etc.) from public resources.
• Implement pipelines using Python and Airflow, and selected R components where appropriate.
• Ensure robustness, reproducibility, and scalability of data processing workflows.

2. PandaOmics Development

• Participate in the development of omics-related product features, collaborating closely with product and engineering teams.
• Implement backend logic using Python and Django.
• Design and extend internal and external APIs used by company products and research teams.

3. Data Management & Infrastructure

• Work with large-scale omics datasets stored in PostgreSQL and AWS S3 as part of the company Data Warehouse (DWH).
• Contribute to data modeling, versioning strategies, and performance optimization.
• Ensure data consistency and traceability across pipelines and product layers.

4. Metadata Annotation & Normalization

• Develop and support data annotation and normalization workflows, including LLM-based agents for metadata curation.
• Collaborate with domain experts to improve annotation quality, coverage, and consistency.

5. Support internal and external collaborations by assisting with:

• Bioinformatics algorithms
• Data processing and analysis
• Interpretation of omics results
• Act as a technical point of contact for omics-related questions within cross-functional teams.

General Requirements:

I. Education

Master s degree or PhD degree in Bioinformatics, Computational Biology, Biology, Computer Science, or a related field.

II. Experience and Skills

• 3-4 years of experience in Python. E.g. for data processing and backend development;
• 3-4 years of experience in OMICs data analysis and biological data formats;
• Advantageously experience building or maintaining data pipelines (e.g., Airflow or similar tools);
• PostgreSQL and cloud storage (preferably AWS S3);
• Effective communicator both orally and in writing English;
• The ability to work autonomously and as part of a team successfully;
• Ability to problem solve and think outside the box.

Nice to Have

• Experience with single-cell omics or large-scale public datasets (GEO, SRA, ArrayExpress, etc.).
• Familiarity with Django REST Framework.
• LLM-based data annotation or automation tools.
• Knowledge of data warehousing concepts and analytical data models.
• Exposure to production-level bioinformatics platforms or biotech products.