Senior Data Science Analyst

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over 2 years old

This job is no longer active

Locations: Boston, San Francisco/Mountain View, Austin, Seattle or Toronto

We are looking for a highly motivated and solution-oriented Senior Analyst to join our Search & Recommendations Analytics team. The team leverages Wayfair’s huge datasets to inform the roadmap of our recommendations. We work in close collaboration with a high performing team of engineers, machine learning engineers/data scientists, and product managers who are on the leading edge of the product recommendation space. Examples of our work are: 

  • Design, run and analyze the results of A/B tests of new recommendation algorithms and strategies; we also develop new testing and test analysis methodologies.
  • KPI reporting and monitoring; this includes anomaly detection tools and advanced measurement approaches.
  • Exploratory data analysis (e.g. clustering/segmentation) to generate new insights & inform our product recommendation roadmap.
  • Use and develop our in-house automated tools; for instance, we have created a QA tool to better understand the performance of our new algorithms before A/B testing them.

What You'll Do

  • Run open-ended exploratory data analysis to identify new ideas and opportunities
  • Design and run A/B tests of our latest recommendations algorithms
  • Proactively monitor our recommendation models to identify potential issues, determine root causes, and resolve. 
  • Build new tools that allow us to be more productive and efficient
  • Work closely and build productive relationships with our product, engineering and machine learning stakeholders.
  • Communicate key insights and recommendations to cross-functional executive leaders across the organization

What You'll Need

  • 1.5+ years of professional experience in an analytical role (in addition to any graduate education).
  • Analytics or Data Science experiences with e-commerce companies is a strong plus.
  • In-depth experience with SQL (aggregate functions, query optimization, stored procedures, string parsing, Vertica/Hive/Presto/Spark, etc.), required.
  • In-depth experience with python & python tools (Jupyter notebooks, functions, pandas, sklearn, matplotlib, etc.), required.
  • Experience with experimental design (A/B tests) and statistical analysis to drive business decision making, highly preferred. 
  • Knowledge and experience using machine learning algorithms/techniques (decision trees, random forest, deep learning, etc.) within a business context, highly preferred. 
  • Strong written and verbal communication with a team player, highly collaborative attitude. 
  • Ability to collaborate and proactively communicate with stakeholders.
  • Proven track record of taking ownership and driving results. Thrive in a fast-paced environment. 
  • Strong business acumen, analytical skills, and technical abilities along with problem-solving skills.

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.