Senior Machine Learning Scientist

Company: Freenome
Location: South San Francisco
Posted on: May 3, 2021

Job Description:

About the Role

The Senior Machine Learning Scientist will be responsible for leading the scientific direction and execution for the development of early, noninvasive detection tests for multiple cancers. They will build on a foundation of Machine Learning, Mathematics, Statistics and Computer Science to incorporate biology in the pursuit of early detection of disease. They will 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.

Responsibilities

• 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

What We're Looking For

• PhD or equivalent research experience in a relevant, quantitative field such as computer science (AI or ML emphasis), statistics, applied math, engineering, or a related field.
• 4+ years of post-PhD or industry experience working on the technical subject matter.
• Expertise, demonstrated by research publications or industrial 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
• A passion for innovation and demonstrated initiative in tackling new areas of research

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

About Freenome

Freenome is on a mission to empower everyone with the tools they need to detect, treat, and ultimately prevent cancer.

We have pioneered the most comprehensive multiomics platform for early cancer detection through a routine blood draw. By combining deep expertise in molecular biology with advanced computational biology and machine learning techniques to recognize disease-associated patterns among billions of circulating, cell-free biomarkers, we are developing simple and accurate blood tests for early cancer detection and integrating the actionable insights into health systems to operationalize a machine learning feedback loop between care and science.

Our recent $270 Million Series C brings our financing to over $500 million from investors, including; Bain Capital, Perceptive Advisors, RA Capital, Polaris Partners, Andreessen Horowitz, funds and accounts advised by T. Rowe Price Associates, Inc., GV (formerly Google Ventures), Roche Venture Fund, Kaiser Permanente Ventures, American Cancer Society's BrightEdge Ventures, Data Collective Venture Capital, Novartis and Verily Life Sciences.

Our Science

Freenome is building technology to advance the understanding of cancer through multiple analytes derived from blood. These signals include cell-free DNA, methylation of cell-free DNA, cell-free RNA, circulating proteins, and immune profiling derived from thousands of prospective samples. By developing novel statistical learning methods and applying them to integrate various -omics datasets, Freenome is a leader in modeling specific biological mechanisms to capture disease-dependent signatures, including gene expression, immune response, tumor burden, the tissue of origin, and 3D chromatin structure.

By building comprehensive discovery datasets and modeling critical biological systems, Freenome is learning what biological changes are present within the blood between a variety of different disease states, including cancer, autoimmune disorders, infections, drug response, and aging. The synthesis of Freenome's datasets, cross-functional technical expertise, and audacious mission to discover biological truth, we seek to improve the lives of millions through early detection and early treatment of disease.

Our Culture

Freenomers are technical, creative, visionary, grounded, empathetic, and passionate. We build teams around divergent expertise, allowing us to solve problems and ascertain opportunities in unique ways. Freenomers are some of the most talented experts in their fields, joining together to advance healthcare, one breakthrough at a time.

We value empathy, integrity, and trust in one another, and we respect the diverse perspectives of our colleagues and those we serve. We assume positive intent and give each other the benefit of the doubt with the firm belief that we are a team working toward the same objectives. We believe in empowering and supporting each other in a collaborative and dynamic environment.

What does a successful person look like at Freenome?

Those who thrive at Freenome prioritize, manage, and execute their own goals with ownership and alignment with those of the company. They embrace our values of empathy, integrity, striving for greatness, servant leadership, trust, and holding themselves and their team accountable to these values. They crave collaboration with brilliant minds from disparate fields of study and believe that hiring and mentorship are fundamental to our success. Above all, they welcome and provide constructive feedback and criticism, trusting in others' good intentions, and being secure in knowing that embracing mistakes is the best way to learn and grow. For those who pursue challenges, understudied problems, and want the opportunity to see their work impact the lives of millions of people affected by cancer every year, there's no better place to be than Freenome.

Freenome is proud to be an equal opportunity employer and we value diversity. Freenome does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law.

Keywords: Freenome, South San Francisco , Senior Machine Learning Scientist, Other , South San Francisco, California