Computational Infrastructure Scientist – Biological Data Systems

Role Summary

Computational Infrastructure Scientist – Biological Data Systems is a scientific engineering role focused on building and extending data systems for large-scale biological and genetic research. The position sits at the intersection of biology, computation, and informatics, designing robust, reusable infrastructure to make biological data usable, reproducible, and scalable across research pipelines. The candidate combines scientific curiosity with engineering discipline to create systems that enable efficient data preparation, integration, and exploration in support of drug discovery and precision medicine.

Responsibilities

• Strategize and implement scientific data processing workflows that transform complex biological datasets into actionable insights.
• Design and develop innovative algorithms and ETL systems to address emerging challenges in biological and drug discovery data integration.
• Collaborate cross-functionally with domain scientists and engineers to translate biological questions into computational frameworks.
• Contribute to the long-term architecture and evolution of the data platform, ensuring scalability, transparency, and reproducibility.
• Develop cloud-based workflows and APIs that enable efficient access and analysis across diverse biological datasets.
• Document and share design decisions to promote reuse and institutional knowledge.

Qualifications

• Required: Strong programming experience in Python and familiarity with R.
• Required: Experience working in Linux environments.
• Required: Knowledge of biological databases, ontologies, and metadata systems.
• Required: Knowledge of PostgreSQL databases.
• Required: Proficiency in Linux environments and Git.
• Required: Exposure to cloud platforms (e.g., AWS S3, EC2, or equivalent).
• Required: Experience working with workflow execution environments including NextFlow.
• Required: Experience developing data-driven decision support applications including data and visual analytical tools.
• Required: Exposure to Docker or containerized environments.
• Required: Strong communication skills and the ability to work independently on open-ended technical problems.
• Preferred: Understanding of web design and API.

Education

• PhD in Computational Biology, Chemistry, Bioinformatics, or a related scientific field.