Data Scientist – Deep Learning at Natera

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Employer: Natera

Expires: 07/31/2020

The Data Scientist will participate in the design and prototyping of cutting-edge deep learning and statistical algorithms for analysis of genetic data.PRIMARY RESPONSIBILITIES:Analyze next-generation sequencing data ranging from single research experiments to commercial data sets of millions of samples.Design novel deep learning architectures for application in genomics.Research and develop machine learning and statistical algorithms for genetic diagnostics. Develop Python software infrastructure to support algorithm testing and simulation studies.Contribute to research and product development efforts.Produce correct conclusions based on rigorous mathematical analysis and principles of statistics and probability.Produce high quality technical documentation including research reports and algorithm specifications.QUALIFICATIONS:Master’s degree in engineering, applied math, statistics, or similar, PhD preferred.At least 2-year practical experience in scientific data analysis using software such as Python.KNOWLEDGE, SKILLS, AND ABILITIES:Knowledge of deep learning techniques and theory.Experience applying deep learning methods (to genomic data a plus).Experience with using CNNs for classification and segmentation a plusProficiency in at least one major deep learning framework, preferably TensorFlow.Strong foundation in probability theory and/or statistics including concepts like joint and conditional probability distributions, parameter estimation and hypothesis testing.Excellent verbal and written communication skills and the desire to work in a dynamic and collaborative environment.Desire to learn about human genetics and sequencing technologies.PHYSICAL DEMANDS & WORK ENVIRONMENT:Duties are typically performed in an office setting.This position requires the ability to use a computer keyboard, communicate over the telephone and read printed material.Duties may require working outside normal working hours (evenings and weekends) at times.