Senior Data 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 both expanding our understanding of how our sales representatives and customers interact to enhance Wayfair’s ability to identify and prioritize the highest value touchpoints along customer journeys. You will own data-driven customer development, generate and operationalize ideas that drive Sales revenue growth, while maintaining a high bar for thoughtful, impactful analysis. You will work collaboratively to apply your findings to develop and prioritize revenue-driving hypotheses we can test to measure impact. In sum, 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, and Excel to wrangle Wayfair’s unique data to create analyses and tools that point to the most significant business growth opportunities
- Break down complex problems into requisite components and iteratively test to improve key metrics
- Work closely with Sales Operations, Product, Marketing, Business Intelligence, Data Science, Pricing and other teams to develop and execute analyses and tests that lead to increased customer insights and accelerate growth
- Become the subject matter expert on multiple Wayfair data sets and experimentation design
- Communicate findings and recommendations with relevant teams and leadership to drive measurable improvements in business impact
Projects Might Include:
- Monitor the revenue and profit dynamics of sales programs, investigate the key drivers of sales incrementality (causal analytics, structural equation modeling), and help develop an actionable strategy to increase revenue and profitability.
- Estimate customer growth and lifetime value by developing and evaluating time series models (e.g. seasonal panel model, seasonal ARIMA, multilevel growth modeling, and structural equation modeling).
- Use Sales Representative click tracking and customer outreach data to quantify the impact of optimizing Sales resource allocation to the most responsive and valuable customer Accounts.
- Personalize the types and number of customers sales representatives should have in their books based on their strengths, customer preferences, and profitability impact.
- Collaborate with an engineering team to implement an internal tool that helps sales representatives better know what action to take with their accounts, when to take them, and with what messaging.
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.
- Experience working with incomplete and dirty datasets and being involved with improving them in a meaningful way.
- Experience with methods & techniques of drawing meaning from data sets and statistical tests.
- Experience with experimental design, implementation, and analysis (split tests, A/B tests, holdout tests, etc…).
- 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.