Senior Machine Learning Scientist (Remote)

This position is open to remote within the US or onsite at our headquarters in South San Francisco, CA.

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, we are seeking a Senior Machine Learning Scientist to help grow the Freenome Computational Science team. The ideal candidate will have a strong foundation in Machine Learning, Mathematics, Statistics and Computer Science to incorporate biology in the pursuit of early detection of disease. You will be responsible for leading the scientific direction and execution for the development of early, noninvasive detection tests for multiple cancers. You will also work with computational biologists, molecular biologists and engineers to drive the iteration of research experiments and become the primary drivers towards Freenome’s mission of solving cancer.

You are passionate about innovation and demonstrated initiative in tackling new areas of research, and you will have a significant impact on the continued growth of a high profile technology organization that is changing the landscape on early cancer detection.

The role reports to our Director of Machine Learning Science.

What you'll do:

• Lead the direction and development of cutting edge research in statistical modeling and inference of biological problems (including cancer research, genomics, computational biology/bioinformatics, immunology, therapeutics, and more)
• Lead research projects that propose new methods and perspectives for modeling various biological changes resulting from diseases such as cancer, autoimmune disease, and infection
• Build and immediately apply core analyses in support of a long term research program in data driven biology
• Interface with product teams to identify potential new problem areas in need of an ML solution
• Take a mindful, transparent, and humane approach to your work

Must haves:

• PhD or equivalent research experience in a relevant, quantitative field such as Computer Science (AI or ML emphasis), Statistics, Mathematics, Engineering, or a related field
• 3+ years of post-PhD or industry experience working on the technical subject matter
• Expertise, demonstrated by research publications or industry experience, in applied machine learning, data mining, pattern recognition, or AI
• Strong knowledge of mathematical fundamentals: statistics, probability theory, linear algebra
• Practical and theoretical understanding of fundamental models and algorithms in supervised and unsupervised learning: generalized linear models, kernel machines, decision trees, neural networks; boosting and model aggregation; clustering and mixture modeling; Bayesian inference and model selection, EM, variational inference, Gaussian processes, causal inference, Monte Carlo methods; dimensionality reduction and manifold learning
• Proficiency in a general-purpose programming language: Python, Java, C, C++, etc
• Familiarity working in a Linux server-based environment
• Excellent ability to clearly communicate across disciplines and work collaboratively towards next steps in experimental iterations

Nice to haves:

• Deep domain-specific experience in computational biology, genomics or a related field
• Experience in scientific parallel computing like an HPE systems, and/or in distributed computing environments like Kubernetes
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems
• Experience in high-performance computing, including SIMD or GPU performance optimization

Benefits and additional information:

The US target range of our base salary for new hires is $165,750 - $225,000. 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)

#LI-Remote