The company is currently seeking a Lead Bioinformatics & Machine Learning Scientist to contribute to research and development within our Bioinformatics Research and Development team, focused on Epigenomics in Oncology. The team develops machine learning methods for early cancer detection from cell-free DNA methylation data. The ideal candidate will have a strong background in machine learning and statistical modeling, as well as genomics and sequencing data analysis. The successful candidate will be instrumental in developing and expanding state-of-the-art machine learning methods for early detection of cancer, and will provide technical leadership and mentorship within a highly collaborative team.
PRIMARY RESPONSIBILITIES:
Drive technical workstreams within a collaborative team that takes methods from problem definition through delivery of final classifiers to downstream validation teams
Design, implement, and validate novel machine learning and statistical methods to solve problems in cancer diagnostics
Establish and promote best practices in model interpretability, uncertainty estimation, and reproducibility
Design robust feature engineering and extraction pipelines tailored to cfDNA methylation and sequencing data
Collaborate closely with molecular biologists on experimental design, ensuring data integrity and quality control
Mentor other scientists and foster a culture of innovation, collaboration, and scientific excellence
Lead and actively participate in code and design reviews
Requirements
PhD in Bioinformatics, Computer Science, Machine Learning, Statistics, or a related quantitative field, with 4 to 8+ years of post-PhD experience
Hands-on experience in cancer genomics or epigenomics; experience with cell-free DNA or methylation sequencing data is a plus
Strong foundation in quantitative reasoning, statistical analysis, and applied machine learning; experience with deep learning frameworks is a plus
Proven track record of developing computational methods for high-throughput sequencing data analysis
Strong programming skills, with hands-on experience in Python and its scientific library stack (pandas, NumPy, scikit-learn)
Experience with Linux command-line tools, shell scripting, version control (Git), workflow managers (e.g., Nextflow, Snakemake), and cloud or HPC compute environments
Ability to perform hypothesis-driven research, visualize findings, and summarize results in oral and written form
Experience mentoring or technically leading other scientists
The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.
Remote USA
$146,000 - $180,000 USD
OUR OPPORTUNITY
The company is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives.
The company team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join the company, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management.
Benefits
Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, the company employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!
For more information, visit the company's site .
The company is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide.
If you are based in California, we encourage you to read this important information for California residents.
Link: the company's site
Please be advised that the company will reach out to candidates with a @ the company's site email domain ONLY. Email communications from all other domain names are not from the company or its employees and are fraudulent. The company does not request interviews via text messages and does not ask for personal information until a candidate has engaged with the company and has spoken to a recruiter and the hiring team. The company takes cyber crimes seriously, and will collaborate with law enforcement authorities to prosecute any related cyber crimes.
For more information:
BBB announcement on job scams
FBI Cyber Crime resource page
Where you’d work
Fully remote
You can work from
United States
About the company
Hidden companyCompany hidden
Industry: HealthTech
Good
Your chances
Still hiring, not crowded yet, and you'd be among the first.
17 checks run
7 good signs
0 red flags
Still hiring?
11 checks
Actively hiring
StaleHiring
In its favour3
Still on the company's own careers site, checked 1 h agoModerate evidence
Found in the last 48 hours, before the big job boardsModerate evidence
A tight salary range, set for one seat: $145K to $180KSlight evidence
How crowded?
6 checks
Low
QuietCrowded
In its favour4
In its Early Window: not on the big job boards yetStrong evidence
Asks for 8+ years: a narrow poolModerate evidence
Asks for scikit-learn, which fewer than 1% of open roles doSlight evidence
1 moreFewer
Pays below most similar roles, which thins the crowdSlight evidence
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