Senior Data Scientist # 4630

Responsibilities

• Envision, design, and lead projects to evaluate and improve machine learning classifier performance for cancer detection
• Collaborate cross-functionally with scientists, engineers, and clinicians to plan, execute, and interpret experiments
• Develop high-quality, reproducible, and scalable software aligned with sound engineering principles
• Apply best practices in machine learning and statistics to generate robust, interpretable, and reliable results
• Analyze large-scale sequencing and genomics datasets to extract meaningful biological insights
• Contribute to the development and evaluation of novel machine learning methods, including deep learning approaches
• Communicate findings and present updates regularly in technical and cross-functional forums
• Contribute to scientific publications, internal tools, and production systems

Qualifications

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, Statistics, Machine Learning, or a related field with 2+ years of relevant experience, OR S.M. with 4+ years of relevant experience, OR B.S. with 6+ years of relevant experience, or equivalent practical experience
• Strong expertise in data analysis using Python or R
• Deep understanding of modern machine learning and statistical methods
• Experience developing reproducible, well-structured code in a collaborative environment
• Strong written and verbal communication skills

Preferred Qualifications

• Experience with modern AI techniques, including deep learning and/or large language model (LLM) training or adaptation
• Experience working with sequencing or genomics data and deriving biological insights
• Track record of scientific contributions (e.g., publications, tools, datasets, patents, or conference presentations)
• Experience with system-level programming languages (e.g., Go, Java, C, C++)
• Familiarity with version control (e.g., Git) and reproducible research practices in Linux environments
• Demonstrated ability to independently drive projects while collaborating effectively across teams
• Interest in translating research innovations into production-ready systems

Pay

The expected, full-time, annual base pay scale for this position is $156,000 - $187,000. Actual base pay will consider skills, experience, and location.

Schedule

This is a hybrid role based in Menlo Park, CA (moving to Sunnyvale, CA in Fall 2026). Our current flexible work arrangement policy requires that a minimum of 40%, or 16 hours, of your total work week be on-site. Your specific schedule, determined in collaboration with your manager, will align with team and business needs and could exceed the 40% requirement for the site.