Senior Data Scientist – Deep Learning

San Francisco, California

  Machine Learning

160000

Permanent

Our client is a targeted precision medicine company for cardiovascular disease. Their mission is to improve access and outcomes for people with heart conditions through bold and innovative science.  They integrate cutting edge clinical science with easy-to-use technology that can predict and establish points of early intervention, to mitigate disease progression and poor outcomes.

What you will do

  • You will be a hands-on individual contributor using your skills at the intersection of deep learning to implement and build on our research plans.
  • You will drive projects from implementation to production development and potentially publication at major conferences (e.g. NeurIPS, ICML).
  • You will set a high technical bar and become an integral ambassador of good practice in building machine learning systems and system architecture.
  • You will work cross-functionally with healthcare providers, epidemiologists, and product managers.

Required Qualification:

  • PhD in computer science or a related field. 
  • 3+ years of industry experience building deep learning systems.
  • You have at least one first author publication in Machine learning or previously led a similarly complex project.
  • You have worked on at least one project using large healthcare data (e.g. claims, EHR).
  • You are proficient in 1+ deep learning framework (e.g. TensorFlow, PyTorch).
  • Experience across the MLOps cycle.
  • You have experience in time series analyses and/or signal processing (e.g. ECGs).
  • Utilize best coding practice, (e.g. functional programming, testing) and motivated by creating clean and reproducible code.
  • Experience with statistical inference and modelling (e.g. t-test, ANOVA).
  • You can work independently and proactively mitigate challenges.
  • You can articulate technical concepts to a non-technical audience.
  • You are eager to constantly learn about new and better tools.
  • You have contributed to a production-facing ML system.

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