As a Senior Data Scientist, you will build machine learning products to help automate workflows and provide valuable assistance to our customers. You’ll have access to the right tools for the job, large amounts of quality data, and support from leadership that understands the full data science lifecycle. You’ll build models using technologies such as Python, Tensorflow, and Docker.

Responsibilities:

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  Interpret and understand business needs/market opportunities, and translate those into production analytics.
  


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  Select appropriate technologies and algorithms for given use cases.
  


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  Work directly with product managers and engineering teams to tightly integrate new analytic capabilities.
  


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  Prepare reports, visualizations, and other documentation on the status, operation and maintenance of the analytics you create.
  


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  Stay current on relevant machine learning and data science practices, and apply those to existing problem sets.
  

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  Excellent understanding of machine learning algorithms, processes, tools, and platforms including: CNN, RNN, NLP, Tensorflow, PyTorch, etc.
  


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  Proficient with the following (or comparable): Linux, Python, scikit-learn, NumPy, pandas, spaCy.
  


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  Applied experience with machine learning on large datasets/sparse data with structured and unstructured data.
  


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  Experience with deep learning techniques and their optimizations for efficient implementation.
  


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  Great communication skills, ability to explain predictive analytics to non-technical audiences
  


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  Bachelor’s in Math, Engineering, or Computer Science (or technical degree with commensurate industry experience).
  


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  3+ years of relevant work experience in data science/machine learning.
  

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  AWS services such as Lambda, AppSync, S3, and DynamoDB
  


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  DevOps experience with continuous integration/continuous deployment.
  


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  Experience in software engineering best practices, principles, and code design concepts.
  


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  Speech-to-text or OCR expertise.
  

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  Has a passion for code quality and craftsmanship.
  


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  Views your profession as your craft and continuously pursues excellence in your work.
  


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  Thrives in a fast-paced, high-growth startup environment.
  


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  Collaborates effectively across various teams, coordinating regularly to set and manage expectations.