Staff Computational Biologist

Freenome

Staff Computational Biologist applying computational biology and statistical models to drive cancer diagnostic innovations at Freenome. Collaborating with scientists to enhance algorithms for identifying cancer signatures.

Posted 7/23/2026full-timeRemote • California • 🇺🇸 United StatesLead💰 $188,275 - $270,375 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates deep expertise in cancer and molecular biology, applying advanced computational techniques for biological discovery and product development. Proficient in statistical modeling and data analysis using programming languages and tools relevant to genomics and proteomics.

Highest-signal resume keywords

PhD In Computational BiologyExtensive Experience In Cancer BiologyProficiency In Python Statistical PackagesExpertise In High-Throughput Data AnalysisDevelopment Of Statistical Models

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Computational BiologyData AnalysisStatistical ModelingGenomicsProteomicsRNA SequencingWhole Genome SequencingMethyl-seqPython ProgrammingMachine Learning

Soft Skills

Thought LeadershipCollaborationMentoringProblem SolvingProject Management

Tools & Technologies

NumpyMatplotlibPandasScikit-learnTensorFlowPyTorch

Industry Keywords

Molecular AssaysCancer DiagnosticsBiological DiscoveryCell-Free Circulating Nucleic AcidsEpigenomicsTranscriptomics

Tech Stack

Tools & technologies

NumpyPandasPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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++.

Benefits

Comp & perks

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.