Senior Data Science Analyst, Data Science Catalog

Boston, MA

Full Time Senior-level / Expert
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Wayfair Inc.
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Wayfair’s Data Science team builds the algorithmic systems that drive our business, enhance customer experience, & improve customer loyalty. The Data Science Catalog team at Wayfair develops machine learning models to: (1) improve customer experience by accurately tagging products using multimodal data sources (image, text, categorical, numeric, etc.), (2) drive catalog and pricing strategy by powering comparisons between large numbers of products, and (3) solve the product cold-start problem to enable customers to find the best new products.

We partner closely with our Merchandising, Engineering, and other Data Science teams in order to build scalable algorithmic systems responsible for predictive modeling that drives business strategy for various merchandising and supplier side teams. 

We are looking for a Senior Analyst to join the Data Science Catalog Analytics team, with an emphasis on ensuring the healthiness of machine learning products. You will be working together with other analysts, data scientists, as well as multiple merch and engineering teams to solve one of our most impactful and intellectually challenging data science problems at Wayfair. 

What You'll Do

  • Integrate tightly into our Data Science workstreams and act as the subject matter expert for data and analytics in the respective domain.
  • Explore, prototype, test and automate data pipelines and provide insights into model performance and business KPI impact 
  • Uncover insights hidden in our vast repository of raw data, and provide tactical guidance on how to act on findings 
  • Deliver presentations to business stakeholders that tell cohesive stories using data and on point visualizations to support data supported decision making and ultimately enhance the experience of our customers and our suppliers

What You'll Need 

  • 2+ years of experience as a data analyst/data engineer with background in a technical/quantitative field (e.g. mathematics, economics, computer science, analytics,  engineering, physics, neuroscience, operations research etc.) 
  • Ability to effectively work with business leads: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business direction
  • Good understanding of how quantitative and technical work aligns closely with business priorities and business value 
  • Understanding of the data analytical stack to build complex reporting and data visualization dashboards using Tableau, Data Studio or redash
  • Experience with programming, e.g. languages such as Python/R and SQL and big data frameworks as Apache suite, GBQ or Hive
  • Ability to work in a dynamic environment where there can be degrees of ambiguity
  • Bonus points for creative curiosity and a strong desire to always be learning 

About Wayfair Inc.

Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.

No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.

Job region(s): North America
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