Who We Are
Wayfair Analytics is the engine that powers an enterprise obsessed with data. We are excited to bring our aspiration of ‘the best two-sided marketplace for home’ to reality by connecting millions of customers and thousands of suppliers across the globe in new ways. This represents a step function change to our model, by unlocking highly motivated suppliers and delighting customers with a tighter, more immersive experience. We will be in a position to better serve our customers across a range of diverse categories, stores and geos, growing our market share substantially.
We are looking for a Staff Product Analyst to join the Partner Home organization, Wayfair’s supplier-facing user experience, supporting Wayfair and our many suppliers globally to reach their growth ambitions. In this role, you will directly partner with teams across Product, Engineering and UX to design on-site tests and analyze user behavior patterns to improve our supplier-facing sites
What You’ll Do
- Work directly with the Engineering team to create entirely new supplier experiences and improve the existing ones.
- Develop a strong understanding of how end users behave through data, using that understanding to define and track KPIs for our supplier experience.
- Become the subject matter expert for data, analytics, and testing of our supplier-facing applications to ensure accurate and proper interpretation of core business metrics and supplier behavior.
- Perform deep-dive analysis, including advanced analytical techniques, to solve some of the more critical and complex business problems including website funnel progression or user segmentation and targeting.
- Shape the product roadmap and recommend improvements by analyzing data from our live products, identifying the most impactful ways for data and analytics to drive decision making and accelerate profitable growth.
- Work alongside partner teams to implement your product recommendations.
- Develop data visualizations, including reports, dashboards, and analyses to distribute data insights in an easily digestible manner to all relevant stakeholders and integration partners.
What You’ll Need
- 5+ years experience in an Analytics, Business Intelligence, Data Science or Engineering role performing quantitative analysis.
- Proficient knowledge of SQL (incl. aggregate functions, joins, etc.) or other structured programming language(s) (e.g. Python, R, JavaScript). Experience with GBQ is a plus.
- Hands-on experience conducting quantitative analyses on large data sets. Experience with Google Data Studio, Looker and Google Analytics 360 a plus.
- Strong written and verbal communication.
- Bachelor’s or Master’s in Computer Science, Computer Engineering, Analytics, Mathematics, Statistics, Information Systems, Economics, Management or other quantitative discipline field with strong academic record.
- Previous Ecommerce or Retail Analytics experience is a strong plus.
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.