Why join Freenome?
Freenome is a high-growth biotech company developing tests to detect cancer using a standard blood draw. To do this, Freenome uses a multiomics platform that combines tumor and non-tumor signals with machine learning to find cancer in its earliest, most-treatable stages.
Cancer is relentless. This is why Freenome is building the clinical, economic, and operational evidence to drive cancer screening and save lives. Our first screening test is for colorectal cancer (CRC) and advanced adenomas, and it’s just the beginning.
Founded in 2014, Freenome has ~500 employees and more than $1.1B in funding from key investors, such as the American Cancer Society, Andreessen Horowitz, Anthem Blue Cross, Bain Capital, Colorectal Cancer Alliance, DCVC, Fidelity, Google Ventures, Kaiser Permanente, Novartis, Perceptive Advisors, RA Capital, Roche, Sands Capital, T. Rowe Price, and Verily.
At Freenome, we aim to impact patients by empowering everyone to prevent, detect, and treat their disease. This, together with our high-performing culture of respect and cross-collaboration, is what motivates us to make every day count.
Become a Freenomer
Do you have what it takes to be a Freenomer? A “Freenomer” is a determined, mission-driven, results-oriented employee fueled by the opportunity to change the landscape of cancer and make a positive impact on patients’ lives. Freenomers bring their diverse experience, expertise, and personal perspective to solve problems and push to achieve what’s possible, one breakthrough at a time.
About this opportunity:
As a Senior Computational Biologist focused on Cancer Biology at Freenome, you will be a key scientific leader in the development of early, noninvasive tests for cancer detection. As a senior member of the team, you will use a strong foundation of the biological mechanisms of cancer to motivate hypotheses, develop, and make improvements to computational algorithms detecting molecular signatures of cancer. You will work closely with and lead the work of machine learning scientists, molecular biologists, and other computational biologists on a collaborative team to drive the iteration of computational models and assays while ultimately developing products which can be used in the clinic.
This role reports to the Director of Computational Biology.
What you’ll do:
- Lead the analysis and interpretation of molecular and clinical data in the context of early cancer detection, serving as a key thought-leader on the computational science team
- Motivate research hypotheses and areas for potential model improvement, and subsequently plan, scope, and execute associated research with a talented team of computational biologists
- Leverage, develop, and apply machine-learning and statistical tools for models development and interpretation
- Remain at the forefront of research developments in cancer biology, including but not limited to early cancer detection and molecular signatures across various types and stages of cancer
- Use foundational knowledge in cancer biology to analyze and interpret data molecular assays such as Mass Spectrometry (MS) and Next Generation Sequencing (NGS)
- Work closely with molecular biologists to collaboratively iterate on experiments in the wet lab
- PhD or equivalent experience in a relevant field such as biology, cancer biology, computational biology, computer science, and other quantitative fields
- 5+ years post-PhD experience applying computational techniques for biological discovery and product development, ideally in industry
- Experience in developing, applying, and evaluating machine learning and statistical algorithms
- Extensive knowledge of cancer biology and molecular biology, with experience leveraging this knowledge for problems in cancer computational biology and diagnostics
- Experience with computational and statistical programming, including experience with Python statistical and machine-learning packages. Equivalents in other languages like R are also suitable
- Strong quantitative reasoning and statistical analysis skills, with a demonstrated ability to apply them effectively to relevant scientific problems
- Experience in the analysis of high-throughput, quantitative technologies in genomics, epigenomics, proteomics, or transcriptomics (e.g. Hi-C, ATAC-seq, RNA-seq, MS)
- Expertise with biological and genomic data, tools, and associated public databases (e.g. ENCODE, TCGA, Blueprint, Cosmic)
- Excellent oral and written communication skills to communicate to both scientific and broader audiences
- Experience mentoring or managing junior scientists, with an ability to work on a cross-functional team (with both computational and experimental scientists)
Benefits and additional information:
The US target range of our base salary for new hires is $157,250 - $240,000. You will also be eligible to receive pre-IPO equity, cash bonuses, and a full range of medical, financial, and other benefits dependent 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 @ https://careers.freenome.com/ 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.