Data Scientist II, Ads

Data Scientist II, Ads

Wayfair is the leading online retailer for furniture & decor and we rely on our suppliers to deliver on our core business proposition: delivering great products to our customers quickly and reliably. Our supplier-facing ecosystem enables our 18,000+ supplier-partners to deliver on that promise by providing them with all capabilities they need to successfully manage their e-commerce business. Our supplier-facing site is a critical enabler to Wayfair's growth. We work with 18K+ suppliers who use our tools daily to manage their products and inventory, order fulfillment, etc. to be successful on our platform.

The Advertising team works with our supplier community creating end to end solutions that help increase their sales and exposure on Wayfair sites and apps through targeted ads and sponsorships. Not only are we generating millions in extra revenue for suppliers and solidifying Wayfair as a preferred partner, but we’ve built a significant business that’s one of the highest growth areas in the company.

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.

What You’ll Need

• Bachelors in computer science, engineering, math, statistics, economics, or other quantitative discipline; Masters preferred.
• 2+ years work experience in quantitative analytics, testing and/or predictive modeling
• Experience in leveraging A/B testing and other experimentation methodologies for effective product launch measurement.
• Experience applying data science techniques such as classification, regression, and clustering; and partnering with business teams on agile model development.
• High comfort level with programming skills in Python and SQL, and experience working with big-data technology such as BigQuery and visualization tools including Looker; ideally familiarity with cloud-based platforms (we use GCP)
• Demonstrated success in communicating with and influencing senior level stakeholders on strategic direction based on recommendations backed by in-depth analysis.