Senior Machine Learning Scientist
Healthcare Data
Posted on 12/30/2022
INACTIVE
Freenome

501-1,000 employees

Blood test cancer detection biotech company
Company Overview
Freenome's mission is to empower everyone to prevent, detect, and treat disease by developing high-quality diagnostic tests. The developing next-generation blood tests powered by their multiomics platform to discover the body’s earliest warning signs of cancer, and develop accessible tests to detect cancer in its earliest, most treatable stages.
AI & Machine Learning
Data & Analytics

Company Stage

Series D

Total Funding

$1.1B

Founded

2014

Headquarters

South San Francisco, California

Growth & Insights
Headcount

6 month growth

4%

1 year growth

13%

2 year growth

44%
Locations
San Bruno, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Kubernetes
Linux/Unix
CategoriesNew
AI & Machine Learning
DevOps & Infrastructure
Requirements
  • Ph.D. and at least four years of academic or industry experience
  • A record of designing and validating creative solutions to complex quantitative problems as demonstrated by research publications or industry achievements
  • Experience working with large, noisy, and confounded datasets
  • Ability to effectively prioritize multiple competing development projects
  • Proficiency in implementing statistical/ML models in a general-purpose programming language
  • Excellent ability to communicate to technical peers and across disciplines, and to work collaboratively on interdisciplinary teams
  • A transparent, self-reflective approach that is comfortable with ambiguity, seeks to improve on or correct flaws in your own work, and is open to others' suggestions
  • A passion for innovation, demonstrated initiative in tackling new areas of research, and an ability to carry great ideas forward to practical and impactful implementation
  • Experience with biological or healthcare data is preferred
  • Facility reading and interpreting scientific and medical literature is preferred
  • Experience with statistical study design is preferred
  • Familiarity working in a Linux environment and with cloud computing infrastructure is preferred
  • Experience in scientific parallel computing and/or in distributed computing environments like Kubernetes is preferred
Responsibilities
  • Be self-directed and innovative contributor: research the literature, apply and test state-of-the-art ML and AI methods, resolve problems, adapt, compare, iterate and collaborate
  • Demonstrate strong command of relevant analytic, ML, AI and biostatistical methods and the ability to find the best approaches for different situations
  • Pursue research on methods and applications while prioritizing the transition of insights to production use
  • Partner closely with the risk modeling scientists, biostatisticians, clinical, and business specialists
  • Present novel scientific results at conferences and in peer-reviewed scientific journals
  • Provide scientific and technical guidance to team members and collaborators while empowering and inspiring them to do their best work
  • Take a mindful, transparent, and humane approach to your work