Senior Decision Sciences Analyst, B2B Insights & Analytics

The B2B Insights & Analytics team is responsible for identifying the most effective means of accelerating revenue growth. With a focus on understanding and improving the impact of proactive sales engagement, we are constantly on the hunt for insights of how our team can unlock growth among new and existing customers.

In this role, you will take ownership of improving the quality - speed & confidence - of our Sales and operational decisions by both expanding our understanding of how we interact with our customers and expanding Wayfair’s ability to identify and prioritize the highest value touchpoints along their journeys. You will own data-driven customer development, generate & operationalize ideas that drive revenue growth, while maintaining a high bar for thoughtful, impactful analysis. You will work collaboratively to apply your findings to develop and prioritize hypotheses we can test to measure the impact of changes in the experience that drive revenue. You’ll be responsible for analyzing data in a meaningful way, synthesizing insights to key stakeholders, and working cross-functionally to implement your findings.

What You'll Do

  • Use SQL, Python, R, Looker, Excel, & Salesforce.com to wrangle Wayfair’s unique data to create analyses and tools that point to the most significant strategies for increasing customer value
  • Break down complex problems into requisite components and iteratively test to improve key metrics
  • Work closely with Data Science, Central Strategy & Operations Team, Measurement & Attribution, Product, Marketing, Business Intelligence, Pricing and other teams to develop and execute analyses and tests that lead to accelerating growth
  • Become the subject matter expert on multiple Wayfair data sets, holistically analyze data signals from across them, and identify key areas for B2B business focus and adaptation
  • Communicate findings and recommendations with relevant teams and leadership to drive measurable improvements in Sales impact

Projects Might Include:

  • Develop driver analyses that intake predictors of a wide range of types - customer firmographic features, Sales interaction experience, customer web behavior, etc. - and identify the most influential variables of customer responsiveness so that Sales can adapt to improve performance through outcome-focused, targeted coaching
  • Collaborate with Sales, Program Management, Training & Communications, Data Science & Sales R&D to develop data driven, personalized Sales coaching frameworks that guide Sales representatives on specific behaviors that maximize incremental impact.
  • Develop granular profitability and Sales efficiency measures to inform on which customers are most valuable, require the most Sales support, and how to better optimize Sales programs through answering opportunity cost trade-offs, etc.
  • Use web browsing behavior to identify customers who are most likely to make a purchase when contacted by a sales representative and quantify the impact of optimizing sales outreach in light of customer behavior.

What You'll Need

  • Experience with driving high impact quantitative analysis leveraging SQL, Python, R, Excel, Looker, Tableau, Git version control, and/or other computational tools.
  • Statistical modeling experience - for example, structural equation modeling, multilevel modeling, growth modeling, forecasting, Bayesian analysis frameworks, network analyses, and/or financial modeling. 
  • Experience with causal analytics and experimental design, implementation, and analysis (split tests, A/B tests, holdout tests, power analyses, etc…).
  • Experience working with incomplete and dirty datasets and being involved with improving them in a meaningful way.
  • High level of curiosity and a propensity for asking (and answering!) questions that begin with “Why”.
  • A passion for analytical work with a high bar for zero defect analysis.
  • Ability to prioritize projects with a focus on business impact, ask questions without hesitation, collaborate seamlessly with cross functional teams, and comfortable sharing your findings and insights!

Who We Are

The B2B Insights & Analytics (I&A) team manages the sustainable growth of the B2B sales program with a focus on creating lasting relationships between customers and our Sales teams. We are comprised of data scientists, statisticians, economists, business analysts, and analytics engineers that have the shared goal of maximizing profitable, incremental sales revenue (i.e. the revenue directly attributable to sales agents that would not otherwise have been captured by Wayfair). To do so, we leverage  Wayfair’s vast data and technology resources, partnering with Sales, Marketing, Program Management, Sales Operations, Training & Communications, R&D (Product & Engineering), Data Science, Business Intelligence, Pricing, Marketing, & Promotions to identify the highest value opportunities for investment.

About Us

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.

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