Description

At Shutterfly, we’re all about people — bringing them together, making them feel welcome, and connecting them to experiences. We make our customers’ memories last a lifetime by capturing, preserving, and sharing them through photography and personalized products. Through our family of brands, trend setting products, cutting edge technology, and best in class customer service, we help our customers, and each other, share life’s joy.

The Shutterfly Personalization Data Sciences Team is recruiting for an exciting role to work with a broad array of machine learning applications from developing computer vision models on billions of images to implementing cutting edge product and content recommendation engines while working with a best-in-class ML ops platform. Our growing team of data scientists and engineers will provide you with the opportunity to work with virtually every form of customer purchase and engagement data, applying state of the art techniques for customer personalization.

What You'll Do Here: 

  • Work with stakeholders to define objectives and measure success, establish KPIs and measurement methodologies
  • Provide expertise to non-analytical peers within Marketing, Product and Engineering
  • Develop experimental designs to support test and learn
  • Apply advanced knowledge of SQL and the ability to extract and develop complex modeling features
  • Size the impact of the models on key business measures
  • Build machine learning models using Python which can recommend optimal product, offer, content and information.
  • Provide actionable insights to drive key decisions across the marketing organization using a range of analytical/statistical techniques from descriptive analysis to predictive/explanatory models
  • Be a self-starter, eager to learn, and motivated by a passion for developing the best possible solutions to problems

The Skills You'll Bring: 

  • MS or Ph.D. or equivalent experience in a quantitative field such as computer or data science, economics, applied statistics or life sciences
  • 3+ years of experience in developing and deploying machine learning and deep learning models in a professional setting
  • Knowledgeable about recent advancement in the field and possess a strong research mindset
  • Domains of expertise should include at least one of the following: collaborative filtering, content-based recommender systems, link-click prediction, NLP for information retrieval, computer vision or predictive customer targeting.
  • Experience with deep learning frameworks such as Tensorflow, Keras and/or Pytorch and developing statistical studies in Python/Jupyter
  • Advanced SQL skills
  • Practical experience with distributed data platforms: Map/Reduce, Hadoop, SPARK
  • Usage of cloud compute solutions, eg. AWS, GCS or Azure
  • Experience with version control systems such as Github
  • Hands-on experience with Unix

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