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.
• 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 through our MLops platform and feature store
• 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
• 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
• Experience with MLops tools and platforms such as MLflow, Sagemaker and DataBricks
• 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 and shell scripting
This position will accept applications on an ongoing basis until filled.
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