Why join Freenome?
Freenome is a high-growth biotech company on a mission since 2014 to create tools that empower everyone to prevent, detect, and treat their disease.
To achieve this mission, Freenome is developing next-generation blood tests to detect cancer in its earliest, most treatable stages using our multiomics platform and machine learning techniques. Our first blood test will detect early-stage colorectal cancer and advanced adenomas.
To fight the war on cancer, Freenome has raised more than $1.1B from leading investors including a16z, GV (formerly Google Ventures), T. Rowe Price, BainCapital, Perceptive Advisors, RA Capital Management, Roche, Kaiser Permanente Ventures, and the American Cancer Society’s BrightEdge Ventures.
Are you ready for the fight? A ‘Freenomer’ is a mission-driven employee who is fueled by the opportunity to make a positive impact on patients' lives, who thrive in a culture of respect and cross collaboration, and whose work makes a significant impact on the company and their career. Freenomers are determined, patient-centric, and outcomes-driven. We build teams around divergent expertise, allowing us to solve problems and ascertain opportunities in unique ways. We are dedicated to advancing healthcare, one breakthrough at a time.
About this opportunity:
At Freenome, our goal is to improve patient outcomes by pioneering the next-generation of blood tests using our combined multiomics and machine learning platform, starting with the early and accurate detection of cancer and continuing to early intervention.
As part of Translational Science at Freenome, you will be joining a multi-disciplinary team partnering with biopharma companies to advance new applications of our platform to improve outcomes in cancer. Example project areas with a focus on early intervention include: (1) identifying molecular subtypes of cancer to add in patient selection for clinical trials/therapies, and (2) discovering predictive biomarkers of therapeutic response from pre-/post-treatment timepoints in pharma trials. As a senior member of the team, you will use a strong foundation of knowledge of the biological mechanisms of cancer and treatments (as well as experience from biopharma) to help advance our team’s research from early planning through to final delivery of results to our partners. As an experienced computational analyst, you will also serve as a technical lead for the team, supporting analysis review and identifying opportunities to scale our capabilities.
This role reports to Vice President, Translational Science.
What you’ll do:
- Lead the analysis and interpretation of molecular and clinical data, particularly in the context of early cancer intervention where Freenome is partnering with biopharma.
- Leverage prior experience working in/with biopharma and in cancer biology, including but not limited to early cancer detection and molecular signatures across various types and stages of cancer; through this knowledge, help to shape our strategic plans and execution of projects.
- Serve as a technical lead / key-thought leader for the translational science team in statistical analyses of data.
- Motivate research hypotheses and areas for potential capabilities improvement, particularly interpretable biological features arising from different multiomics data types; subsequently plan, scope, and execute associated research with a talented team of computational biologists and wet lab scientists.
- Leverage, develop, and apply machine-learning and statistical tools for model development and interpretation.
- PhD or equivalent experience in a relevant field such as computational biology, computer science, and other quantitative fields.
- 6+ years post-PhD experience applying computational techniques for biomarker discovery and product development, ideally in industry.
- Extensive knowledge of cancer biology and molecular biology, with experience leveraging this knowledge for problems in cancer computational biology and diagnostics.
- Strong quantitative reasoning and statistical analysis skills, with a demonstrated ability to apply them effectively to relevant scientific problems.
- Experience in developing, applying, and evaluating statistical and/or machine learning algorithms.
- Experience with computational and statistical programming, including experience with Python statistical and machine-learning packages. Equivalents in other languages like R are also suitable.
- Experience in the analysis of 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 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/hourly rate for new hires is $182,750 - $280,000. 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.
- Family & Medical Leave Act (FMLA)
- Equal Employment Opportunity (EEO)
- Employee Polygraph Protection Act (EPPA)