As a Staff Bioinformatic Research Engineer and Senior Manager at Freenome, you will lead a team responsible for developing and deploying bioinformatics research on Freenome’s ML research platform. You will lead and manage a team of Research Engineers working large multi-omic datasets, including whole-genome sequencing of cell-free DNA, extracellular small RNAs, and circulating proteins to drive diagnostics that impact patients’ lives.
Research engineers are part of an interdisciplinary Science team, working in close collaboration with computational biologists, molecular scientists, machine learning scientists and software engineers to build cutting edge solutions at the intersection of machine learning, genetic sequencing technology, biological data, and distributed systems. These contributions will drive our mission to diagnose cancer at its most actionable and early stages.
As a manager, you will provide strong technical guidance to team members, growing and empowering them to do their best work, while also serving as a mentor in career growth and development.
How you’ll contribute:
- Lead and contribute to the development of Freenome’s bioinformatics research framework to model various biological changes resulting from diseases such as cancer, autoimmune disease, and infection.
- Drive the development of the research platform so that the bioinformatics, in conjunction with machine learning systems, will enable rapid evaluation of scientific hypotheses.
- Connect the biological research that leverage computational biology fundamentals related to NGS or multi-omic data sources to the production system that will process patient samples at scale.
- Support the growth of and build a team of research engineers who are empowered to accelerate scientific discovery by building off a robust research platform.
- Inspire a culture of scientific innovation, translating discoveries into high-impact clinical applications.
- Partner with other scientific leaders at Freenome to develop a scientific roadmap and research strategy, as well as cross-functionally in the scientific planning and execution of collaborative projects.
- Work at the intersection of machine learning research, computational biology, statistics and software engineering.
What you’ll bring:
- 5+ years of experience with bioinformatics infrastructure, automation, and software engineering
- 2+ years of experience managing and mentoring computational scientists.
- PhD or B.S. or M.S. with equivalent experience in a relevant, quantitative field such as computational biology, cancer biology, statistics, bioinformatics, computer science, or equivalent.
- Robust history of delivering major technical projects or analyses, including experience in a technical leadership role.
- Strong computational and programming skills, in Python or equivalent, including thorough experience with large scale systems and user bases. Experience in applying statistical methods and algorithms to large-scale datasets.
- Fundamental understanding of bioinformatics, including the central dogma, molecular or cancer biology, or familiarity with regulatory processes. Experience in analyzing one or more of the following biological modalities: genomics, epigenomics, proteomics (including mass spectrometry), transcriptomics (RNA-seq), Hi-C, ATAC-seq, immunodetection assays are also extremely helpful.
- Track record of selflessly supporting and growing highly effective teams.
- Demonstrated ability to partner with laboratory and computational scientists and engineers to translate scientific roadmaps into concrete products.
- Ability to operate in a highly cross-functional environment where collaboration across disciplines is absolutely necessary.
Freenome has adopted a COVID-19 vaccination policy to safeguard the health and well-being of our employees. As a condition of employment, our employees working on-site are required to be fully vaccinated for COVID-19, unless a reasonable accommodation is approved or as otherwise required by law.
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.
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.
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.
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