Computational Team Member - Bioinformatics focus

About Our Company

We are an innovative biomedical data company dedicated to helping healthcare institutions realize the full value of their biobanks. Through trusted, long-term partnerships, we are building a secure, de-identified repository of clinical and molecular data designed to accelerate precision medicine research. Our platform integrates streamlined biobanking with advanced data analytics, enabling faster diagnostics and the development of breakthrough therapies.  Founded in 2022, we are supported by leading investors including S32, Breyer Capital, Founders Fund, and JSL Health Capital.

Role Overview

We're expanding our computational team, where our core work spans three domains: Machine Learning, Bioinformatics and Software Engineering. We are seeking highly motivated, versatile professionals with demonstrated expertise in bioinformatics and computational biology, and the capacity to grow rapidly to become key contributors in the complementary areas.

We believe a small team can operate with speed, precision and efficiency by leveraging modern productivity tools. We expect you to:

• Broaden Your Knowledge Base – Rapidly learn new biological concepts, technologies, and computational approaches outside your primary area of expertise.
• Leverage Modern AI Tools – Utilize AI-assisted development tools to accelerate implementation while maintaining scientific rigor and technical excellence.
• Think Critically – Serve as the final scientific reviewer of analyses, algorithms, and AI-generated outputs to ensure accuracy and reliability.
• Take Ownership – Drive projects independently while collaborating effectively across disciplines.

Key Responsibilities

We are seeking a bioinformatics scientist who combines strong scientific rigor with practical software engineering skills and thrives in a fast-paced startup environment where innovation, ownership, and cross-functional collaboration are essential. The main responsibilities include:

• Analyze large-scale multi-omics datasets, including cell-free RNA, DNA, and associated clinical data. Perform exploratory analyses, hypothesis generation, feature engineering, quality control and biomarker discovery.
• Design, validate, and optimize bioinformatics algorithms and statistical methods to address challenges in cancer detection and disease monitoring.
• Develop and maintain robust, reproducible, and scalable computational tools and workflows for research, translational, and validation studies.
• Apply software engineering best practices including version control, testing, code review, documentation, and CI/CD principles.
• Improve infrastructure supporting experiment tracking, data management, reproducibility, and quality assurance.
• Evaluate emerging technologies, methodologies, and data sources to improve platform performance and scientific capabilities.

Importantly, the ideal candidate will play a key role in product development and validation, regulatory support, and external collaboration programs:

• Contribute to study design, experimental planning and statistical analysis strategies.
• Support documentation, traceability, verification and validation activities required for regulated research and diagnostic environments.
• Work with academic, clinical, and industry partners on joint R&D initiatives, ensuring high-quality analyses and timely delivery of results.
• Translate biological insights into actionable computational strategies and communicate findings to scientific, clinical and business stakeholders.

Required Qualifications

• Ph.D. or M.S. in Bioinformatics, Computational Biology, Computer Science, Statistics, Genomics, or a related quantitative field.
• 4+ years of relevant industry and/or academic experience in bioinformatics or computational biology.
• Strong background in statistical analysis, algorithm development, and biological data interpretation.
• Demonstrated experience analyzing multiomics data and working with common genomic data formats (FASTQ, BAM, BED, VCF).
• Proficiency in Python and hands-on experience with scientific computing libraries and data analysis frameworks.
• Experience developing reproducible computational pipelines and workflows.
• Strong understanding of software engineering best practices, including Git, testing, code review, documentation, and CI/CD.

Level Expectations

• Member - Leads projects of moderate scope within a team; supports cross-functional work through collaboration. Salary range: $125,000-$155,000.
• Senior Member - Leads complex projects across teams; uses broad business knowledge to drive outcomes beyond immediate function. Salary range: $150,000-$187,000.