Staff Computational Biologist, Translational Science (Remote)

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Why join Freenome?

Freenome is a rapidly expanding biotech company developing tests to detect cancer using a simple blood draw. Freenome employs a multiomics platform that combines signals from cancerous and non-cancerous sources, coupled with machine learning, to detect cancer in its earliest, most treatable stages.

Cancer is relentless. That's why Freenome is constructing the clinical, economic, and operational evidence required to push cancer screening forward and save lives. Our first screening test targets colorectal cancer (CRC) and advanced adenomas, but this is just the beginning.

Launched in 2014, Freenome has approximately 500 employees and has raised over $1.1B in funding from major 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' lives by capacitating everyone to prevent, detect, and treat their disease. This vision, in tandem with our high-performing culture of respect and collaborative work, inspires us to make every day count.

Become a Freenomer

Are you fit to be a Freenomer? A “Freenomer” is a determined, mission-driven, results-focused employee who is inspired by the possibility of altering the landscape of cancer treatment and positively impacting patients' lives. Freenomers apply their diverse experiences, expertise, and viewpoints to solve problems and strive to achieve the impossible, one breakthrough at a time.

About this opportunity:

At Freenome, we aim to enhance patient outcomes by pioneering the next generation of blood tests using our combined multiomics and machine learning platform. We're starting with early and accurate detection of cancer and progressing towards early intervention.

As a member of the Translational Science team at Freenome, you will join a multidisciplinary group partnering with pharmaceutical companies to advance new applications of our platform that will improve cancer outcomes. Example project areas with a focus on early intervention include: (1) identification of molecular subtypes of cancer to aid in patient selection for clinical trials/therapies, and (2) discovery of predictive biomarkers of therapeutic response from pre-/post-treatment timepoints in pharmaceutical trials. As a senior member of the team, you will utilize a robust understanding of cancer biology and treatments (as well as experience from biopharma) to advance our team's research from early planning to final delivery of results to our partners. As a seasoned computational analyst, you will also serve as a technical lead for the team, supporting analysis review and identifying ways to enhance our capabilities.

What you’ll do:

  • Oversee the analysis and interpretation of molecular and clinical data, particularly in the context of early cancer intervention in which Freenome is collaborating with pharmaceutical companies
  • Put to use prior experience in working with biopharma and in cancer biology, including but not limited to cancer diagnosis and molecular signatures across various types and stages of cancer; use this knowledge to help shape our strategic plans and execution of projects
  • Act as a technical lead / key-thought leader for the Translational Science team in the statistical analysis of data
  • Inspire research hypotheses and areas for potential capability improvement, particularly interpretable biological features derived from different multiomics data types; afterward, plan, scope, and execute related research with a skilled team of computational biologists and wet lab scientists
  • Use, develop, and apply machine-learning and statistical tools for model development and interpretation
  • Present analyses clearly and concisely to and lead discussions with a variety of scientific and non-scientific audiences, including both internal and external partners

Must haves:

  • PhD or equivalent experience in a relevant field such as computational biology, computer science, or other quantitative fields
  • 6+ years post-PhD experience working in industry, preferably in biopharma, implementing computational techniques for biomarker discovery and product development
  • Comprehensive knowledge of cancer biology and molecular biology, with experience applying this knowledge in cancer computational biology and diagnostics
  • Strong quantitative reasoning and statistical analysis skills, demonstrated effectively to relevant scientific problems
  • Experience developing, applying, and evaluating statistical and/or machine learning algorithms
  • Experience with computational and statistical programming, including expertise with Python statistical and machine-learning packages. Equivalents in other languages like R are also satisfactory
  • Experience in analyzing high-throughput, quantitative technologies in genomics, epigenomics, proteomics, transcriptomics, or immunomics (e.g., Hi-C, ATAC-seq, RNA-seq, immunoassays)
  • Expertise with biological and genomic data, tools, and related public databases (e.g., ENCODE, TCGA, Blueprint, Cosmic)
  • Excellent oral and written communication skills for communicating with both scientific and broader audiences
  • Experience mentoring or managing younger scientists, with the capability to work in a cross-functional team (with both computational and experimental scientists)

Benefits and additional information:

The target range for our US-based new hires' base ranges from $183,000 to $280,000. You will also be eligible for pre-IPO equity, cash bonuses, and a comprehensive range of medical, financial, and other benefits, depending on the specific position offered. Please note that individual total compensation for this position will be determined solely by the Company and may vary based on factors like location, skill level, years, and depth of relevant experience, and education. Kindly visit our career page @