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Wayfair Analytics is the engine that powers an enterprise obsessed with data. The Wayfair websites generate over 100M clicks from the millions of customers that visit our sites every day to discover and purchase home goods. The Advanced Analytics & Insights team is focused on understanding and optimizing customer behavior on the website and mobile application as a key enabler for the company to move fast and iterate quickly on big business problems.
At their core, the Advanced Analytics & Insights team at Wayfair are strong in quantitative analysis, enjoy coding but also want to balance that with their interest in business and applying advanced modeling techniques. They think critically to tackle complex challenges, thrive in a fast-paced environment and are seeking a high-growth opportunity where they will have an immediate impact on day one. There are significant opportunities for new team members to emerge as leaders, taking on additional projects and responsibilities with strong performance.
What You’ll Do:
- Construct optimized code that massages information from multi-terabyte data sources including sales, clickstream, logistics, product, and customer databases to deliver business insights and recommendations.
- Collaborate with all facets of the organization including product management, engineering, and creative design to identify the most impactful ways for data and analytics to drive decision making and accelerate profitable growth.
- Become the subject matter expert for data, analytics, and testing for your area to ensure accurate and proper interpretation of core business metrics and consumer behavior.
- Design, execute and analyze A/B tests to make high-impact changes to the customer experience.
- Perform deep-dive analysis, including the application of advanced analytical techniques, to solve some of the more critical and complex business problems.
- Develop data visualizations, including reports, dashboards, and analyses in Looker and GBQ to distribute data insights in an easily digestible manner.
What You Have:
- Masters degree in Computer Science, Computer Engineering, Analytics, Mathematics, Statistics, Information Systems, Economics, or other quantitative discipline.
- 6+ months of work experience in a relevant field, such as analytics or data science.
- Proficient knowledge of a statistical programming language such as Python, R, SAS, or SPSS.
- Proficient knowledge of SQL (incl. Aggregate functions, joins, etc.).
- Experience conducting quantitative analyses on large and complex data sets.
- Experience in leveraging modeling algorithms to derive business insights.
- Experience with experimental test design such as A/B testing.
- Experience with data visualization software (e.g. Google Data Studio, Tableau, PowerBI); experience with Looker a plus.
- Analytical, creative, and innovative approach to solving problems.
- Strong written and verbal communication.
- Ecommerce or retail analytics experience a 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.