Who We Are:

Shopping for the home is often overwhelming. Wayfair is an extreme case - it’s visited by two million people daily, shopping across more than 10 million products: Home furnishings, décor, home improvement, housewares, and more. We work hard to conceal the complexity of this experience. Every customer should come away feeling like they’ve found the perfect item for them. Shopping for the home should be exciting, and we’re the team that makes that happen.

 

Successful candidates will be placed into key functions across the business dependent on a combination of interest, skills and experience. Functional areas of interest and potential team placements include:

Business Intelligence is the engine that powers an enterprise obsessed with data. We move fast, iterating quickly on big business problems. We work smart, applying technology to unlock insights and provide outsized value to our customers. We swing big, knowing our customers won’t benefit from micro optimizations. Leveraging the largest data set for products sold in the Home space, this team treats data as an asset and determines how to maximize its business value and extend our competitive advantage.

Merchandising Analytics partners with the Merchandising department as it continues our ambitious plan to build the best online catalog for all things home. In a dynamic, cross-functional and collaborative work environment, the Merchandising Analytics team uses data to drive highly valued insights with the mission to inform decision-making with standardized metrics and KPIs, and increase departmental efficiency through process optimization and automation.

Marketing fuels growth by introducing new customers to Wayfair and driving engagement from our loyal customer base. We drive profitable top line revenue growth by making investments that will drive the greatest return for the business and leveraging our understanding of the customer to drive the overall business strategy. We work cross-functionally with Engineering and Product Management teams to build our own ad tech platforms and partner closely with innovative companies in the tech space such as Google and Facebook to test and explore new opportunities.

 

What You’ll Need:

  • Experience with Excel; coursework or experience with SQL or other structured programming language(s) (e.g. Python, Java, C); and Tableau is a plus
  • Analytical, creative, and innovative approach to solving problems as well as a desire to make processes better
  • Hands-on experience conducting quantitative analyses on large data sets 
  • Strong written and verbal communication in English
  • Bachelors or Masters in Computer Science, Computer Engineering, Analytics, Mathematics, Statistics, Information Systems, Economics, or other quantitative discipline field with strong academic record
  • An entrepreneurial spirit and mindset 
  • Enthusiasm with ability to rapidly get up to speed with job knowledge

 

About Us: 

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.

 

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