Member of Computational Team, Bioinformatics Focus

Exai Bio
Location
Palo Alto, CA
Job Type
Full-time
Posted
July 16, 2026
Views
5
Salary Range
$125k - $187k USD

Job Description

We're Exai Bio — an R&D-stage startup developing next-generation, AI-powered cancer detection assays. Our platform integrates proprietary deep learning AI modeling with unique, large-scale cell-free DNA and RNA (oncRNA) datasets to enable earlier, more accurate cancer detection. We operate with a "small team, broad impact" philosophy: each team member is entrusted with system-level ownership. Our core work spans Machine Learning, Bioinformatics and Software Engineering.

What You Will Do

We are seeking a bioinformatics scientist who combines strong scientific rigor with practical software engineering skills. Responsibilities:

  • Analyze large-scale multi-omics datasets, including cell-free RNA, DNA, and associated clinical data — exploratory analyses, hypothesis generation, feature engineering, QC, and biomarker discovery.
  • Design, validate, and optimize bioinformatics algorithms and statistical methods for cancer detection and disease monitoring.
  • Develop and maintain robust, reproducible, scalable computational tools and workflows for research, translational, and validation studies.
  • Apply software engineering best practices (version control, testing, code review, documentation, CI/CD).
  • Improve infrastructure for experiment tracking, data management, reproducibility, and QA.
  • Contribute to study design, statistical analysis strategies, regulatory documentation/traceability (V&V), and external academic/clinical/industry collaborations.

Who You Are

  • 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.
  • Experience analyzing multiomics data and common genomic formats (FASTQ, BAM, BED, VCF).
  • Proficiency in Python and scientific computing libraries; reproducible pipelines; Git/testing/CI/CD.

Level Expectations

  • Member: leads projects of moderate scope. Salary range: $125,000-$155,000.
  • Senior Member: leads complex projects across teams. Salary range: $150,000-$187,000.

Hybrid team structure with remote work flexibility; new-hire stock option grants, 401(k) with match, medical/dental/vision, 24 days PTO+sick to start.

Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The job is located in Palo Alto, CA, and the company operates with a hybrid team structure that offers remote work flexibility.
What are the key responsibilities of this role?
You will analyze large-scale multi-omics datasets, design and optimize bioinformatics algorithms, and develop scalable computational workflows. You will also apply software engineering best practices, improve data infrastructure, and contribute to study design, statistical analysis, and regulatory documentation.
What qualifications and experience do I need to apply?
You need a Ph.D. or M.S. in Bioinformatics, Computational Biology, or a related quantitative field, plus 4+ years of relevant experience. Proficiency in Python, statistical analysis, multiomics data analysis, genomic formats, and reproducible pipelines is required.
What is the salary range for this position?
The salary range is $125,000 - $155,000 for the Member level, and $150,000 - $187,000 for the Senior Member level.
What benefits and compensation packages are offered?
Benefits include new-hire stock option grants, a 401(k) with company match, medical, dental, and vision insurance, and 24 days of PTO plus sick leave to start.

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Job Information

Source: manual
AI Relevance: 95/100 (Highly relevant)
Remote Type: hybrid
Experience: Mid
Allowed Locations: Worldwide
Skills & Tags:
bioinformatics computational biology multi-omics cell-free RNA biomarker discovery cancer detection liquid biopsy Python algorithms

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