Lead Analyst, Storefront Product Analytics
Wayfair Storefront 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 Storefront Advanced Analytics & Insights team is focused on understanding and optimizing customer behavior as a key enabler for the company to move fast and iterate quickly on big business problems.
This is an ideal opportunity for a high-performing individual contributor passionate about deepening their technical expertise, having increased responsibilities and impact on the businesss bottom line, and growing their career up the technical career ladder. The successful candidate will have excellent technical and analytical skills as well as the ability to present their data driven recommendations in a clear, concise, and persuasive manner.
What You'll Do
- Own and develop the strategic analytic agenda to unlock insights and guide the business.
- Work closely with all facets of the organization including product management, engineering, and creative design to leverage data and analytics to drive decision making and accelerate profitable growth.
- Leverage your modeling skills and apply data science techniques to solve ambiguous problems.
- Bring your expertise in A/B testing to identify, design, execute, and analyze tests leveraging bayesian or frequentist methodologies to make high-impact changes to the customer site and app experiences.
- Communicate key insights and recommendations to cross-functional executive leaders across the organization.
- Be the go-to technical and analytical expert for junior analysts on the team.
- Provide leadership on corporate initiatives which requires the ability to work with executives and be a thought partner with the cross functional leadership team.
What You'll Need
- Bachelors in computer science, engineering, math, statistics, economics, or other quantitative discipline; Masters preferred.
- 4+ years work experience in quantitative analytics, testing and/or predictive modeling
- Experience proactively identifying areas where analytical efforts can add strong business value and setting the analytics roadmap.
- Expert at experimental test design including A/B testing; experience with multivariate and multi-armed bandit also preferred.
- Experience applying data science techniques such as classification and feature modeling; and partnering with business teams on agile model development.
- Proficient knowledge of a statistical programming language such as Python or R.
- Experience working with large data sets and visualization software. Experience in GBQ, Looker a plus.
- Demonstrated success in communicating with and influencing senior level stakeholders on strategic direction based on recommendations backed by in-depth analysis.
About Wayfair Inc.
Wayfair is one of the worlds 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, were 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 youre looking for rapid growth, constant learning, and dynamic challenges, then youll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. Were 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. Thats why were 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.