Promotion Analytics Manager

This is a full-time, hybrid position based in Boston. The role requires four days on-site per week (Monday–Thursday), with remote work on Fridays.

Who We Are

Wayfair is THE destination for all things home: helping everyone, anywhere create their feeling of home.

Wayfair’s Promotions team aims to improve the buying experience for our customers by ensuring they can find the perfect item for them. Our Promo Analytics team partners with teams across brands and channels to help put the right items in front of customers and market them effectively. We combine business understanding, analytics, and technical partnership to improve promotional decisions and build tools that make successful programs easier to measure and scale.

We are looking for an Analytics Manager to lead this work. You will influence decisions across Promotions and partner teams, lead and develop analysts, and work with business and engineering leaders to turn complex needs into actionable insights and durable data solutions.

What You’ll Do

• Own the analytics roadmap for Promotions, aligning team priorities, measures of success, and delivery plans to business goals and promotional priorities.

• Partner with Promotions leaders and senior business decision makers to frame ambiguous questions, evaluate options, quantify impact and tradeoffs, and recommend actions.

• Lead analysis of promotional programs and campaigns, using performance data and experimentation to identify what is working, diagnose drivers, and shape future assortment, offers, merchandising, and marketing decisions.

• Communicate clear, concise, actionable findings to senior leadership and partners across merchandising, marketing, operations, and other teams, adapting the narrative to different levels of technical expertise.

• Lead, coach, and develop analysts by setting priorities, delegating meaningful ownership, providing feedback, and building the team’s ability to deliver high-quality work independently.

• Partner end to end with Data Engineering, BI, Product, and other technical teams: translate business needs into data requirements, metric definitions, data contracts, and acceptance criteria, then help drive build, validation, and adoption.

• Build, prototype, or guide scalable data solutions—including datasets, dashboards, reporting, and automated workflows—that reduce manual effort and support timely business decisions.

• Apply technical judgment and, as needed, hands-on analysis to validate data and logic, investigate data-quality issues, and ensure solutions are accurate, reliable, and fit for their intended use.

• Develop self-serve tools, documentation, and processes that help business partners use data effectively and reduce recurring ad hoc work.

What You’ll Need

• Bachelor’s degree in analytics, statistics, economics, mathematics, business, or a related quantitative field.

• 5+ years of progressive experience in analytics, business intelligence, data science, or a related quantitative role.

• Experience leading analytics work through a team, including coaching or managing analysts, setting priorities, and developing others’ capabilities.

• Strong SQL skills and experience working with large datasets in a cloud data warehouse; Google BigQuery or a comparable platform is a plus.

• Experience developing or guiding data visualizations, reporting, and data solutions using tools such as Looker, Tableau, or Power BI.

• Demonstrated ability to influence business decisions through clear written and verbal communication, including presentations to senior leaders.

• Experience partnering with engineering or other technical teams to scope, build, validate, and maintain data solutions.

• Strong business acumen, quantitative judgment, and problem-solving skills, including the ability to make sound recommendations amid ambiguity and competing priorities.

Nice to Have

• Familiarity with Python or R, data transformation tools such as Dataform, and version control or collaborative development workflows such as Git.

• Experience with experimentation, incremental impact measurement, forecasting, recommendations, or optimization.

• Experience in retail, e-commerce, promotions, pricing, merchandising, or campaign analytics.

• A track record of automating recurring analysis and reporting or enabling business partners to self-serve.