Staff Computational Biologist
Freenome is hiring a Staff Computational Biologist for a remote role. It pays $188k-$270k a year and Level rates it ; you can apply on Freenome.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- The posting lists this role as remote.
- Tools and skills the posting cites include PyTorch, TensorFlow and scikit-learn.
- Level classifies it as a senior role.
- Level lists 29 other open roles at Freenome.
AI in this role
Develop computational models and algorithms to identify molecular signatures of cancer using genomic and sequencing data.
About this opportunity:
At Freenome, we are seeking a seasoned Staff Computational Biologist to help grow the Freenome Computational Science team. The ideal candidate is an expert in computational biology, genomics, and modeling, with a proven track record in industry settings. In this role, you will apply your background in computational biology and statistics to drive the creation of new applications and enhance algorithms for identifying molecular signatures of cancer. You will collaborate closely with machine learning scientists and computational biologists to iteratively advance computational models and assays, playing a key role in bringing products to the clinic. By joining us, you will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.
The role reports to the Manager and Staff Computational Biologist leading genomics modeling within Computational Science. This position can be onsite, hybrid, or remote (US only), based out of our campus in Brisbane, California.
What you’ll do:
- Serve as a key thought-leader on the Computational Science team, leading the analysis and interpretation of cancer's molecular signatures and staying current with the field.
- Guide and contribute to the development of models that characterize biological changes associated with cancer.
- Execute rigorous computational analyses on data from best-in-class molecular assays, including whole genome sequencing, whole genome bisulfite sequencing, targeted sequencing, RNA sequencing, and protein quantitation.
- Design novel statistical models for the evaluation, characterization, and modeling of these data types within the context of cancer biology and progression.
- Identify research hypotheses and potential areas for model improvement; plan, scope, and execute associated research projects with a skilled team of computational biologists.
- Solve complex analytical challenges inherent to the study of cell-free circulating nucleic acids and proteins.
- Partner closely with molecular biologists to collaboratively refine wet lab experiments, and with development scientists to turn research models into products.
- Support the professional development and career growth of talented, cross-functional computational biologists within your team.
Must haves:
- PhD or equivalent experience in a relevant quantitative field (e.g., computational biology, cancer biology, statistics, bioinformatics).
- At least 8 years of post-PhD experience applying computational techniques for biological discovery and product development, preferably in cancer or diagnostics within an industry setting.
- Deep expertise in cancer and molecular biology, with a proven ability to leverage this knowledge for computational biology and diagnostics problems in cancer.
- Extensive experience analyzing data and developing models for high-throughput, quantitative technologies in genomics, epigenomics, transcriptomics, proteomics, (e.g., Methyl-seq, ATAC-seq, RNA-seq, Hi-C, immunodetection assays).
- Proficiency in computational and programming skills, including extensive experience with Python statistical packages (Numpy, Matplotlib, Pandas) and modeling packages (Scikit-learn, TensorFlow, PyTorch) or equivalents in languages like R or C/C++.
Nice to haves:
- Experience training, evaluating, or applying biological sequence models—specifically sequence-to-function models that learn and predict functional biology directly from raw DNA, RNA, or protein sequences.
- Experience developing or applying single-cell genomic or transcriptomic models to translate biological heterogeneity into generalizable regulatory or epigenomic signatures.
- Experience modeling cell-free DNA (cfDNA) signals specifically for early disease detection and diagnostic applications.
Benefits and additional information:
The US target range of our base salary rate for new hires is $188,275 - $270,375. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered. Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.
Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.
Applicants have rights under Federal Employment Laws.
- Family & Medical Leave Act (FMLA)
- Equal Employment Opportunity (EEO)
- Employee Polygraph Protection Act (EPPA)
California applicants please review the CCPA Notice at Collection here:
#LI-REMOTE
How we rate this
Staff Computational Biologist at Freenome rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where computational biology was part of your work. What did you do?
- Tell me about a project where genomics was part of your work. What did you do?
- Tell me about a project where statistical modeling was part of your work. What did you do?
- Tell me about a project where cancer biology was part of your work. What did you do?
- Walk me through how you've used PyTorch in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Computational Biology, Genomics, Statistical Modeling, Cancer Biology, and PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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