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Senior Data Scientist

  • Job type: Permanent
  • Location: New York
  • Salary: Negotiable
  • Job reference: 337591/001_1562960484
  • Sector: BI & Big Data, Glocomms
  • Date posted: 12/07/2019

Senior Data Scientist

San Diego, CA

Artificial Intelligence Startup

Compensation: $120,000-$160,000

(Unlimited PTO, Daily Catered Lunches, Free Gym Membership)

This innovative and well-established IT organization is actively looking to add Senior Data Scientist to their Analytics team. Using their proprietary framework, they are able to help patients recover better, faster, within a more affordable structure. Today, they are working with some of the largest healthcare players in the country to impact millions of patient lives. The right candidate should be up to the challenge of blending the fast-changing technology of big data analytics within the complex space of IT. You will report to the Senior Manager; whose team assist the businesses decisions using Big Data technology and machine learning techniques.

You will be responsible for:

  • Perform complex statistical analyses on large data sets of unique psychometric data

  • Refine our base algorithm that translates psychometric data into actionable insights for our customers

  • Leverage large quantities and diverse sets of behavioral data to drive our proprietary machine learning algorithm

  • Incorporate the latest findings from machine learning and psychological research into a working product

  • Support our research and development roadmap to advance our machine learning algorithm at the core of our (future) products

Minimum Qualifications:

  • MS in Computer Science, Physics, Computational Neuroscience, or related field

  • 4+ years of highly relevant practical experience in data science or data engineering

  • Experience with a wide variety of machine learning models and techniques (e.x. supervised and unsupervised learning, dimensionality reduction)

  • Excellent command of Python and relevant libraries (Numpy, Scipy, Sklearn, etc.)

  • Strong understanding of the fundamental mechanics of machine learning algorithms

Ideal candidates will:

  • Familiar with modern infrastructure and tools (e.g. Kubernetes, Docker, AWS) and large-scale data processing technologies (e.g. SQL, Hadoop, Spark)

  • Knowledge of modern deep learning frameworks and libraries (Tensorflow, PyTorch, Theano, etc.

  • Familiar with and interest in psychometric data

  • Experience in a fast-paced, startup environment

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