Data Scientist III

Data Scientist III, Customer Technology

Wayfair Data Science 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 Customer Tech Data Science 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.

The Customer Tech Data Science team aims to unlock & enable high quality Storefront insights and data capabilities at scale, driven by a robust and extensible platform of self-service capabilities across Customer Technology technology resulting in a higher-impact data-driven organization. Our customers are internal Wayfair teams. Specifically all teams and cross-functional partners on Storefront as well as teams who want to use Storefront-produced data to derive insights and take data-driven actions.

As a Data Scientist III for Customer Tech, your goal is to unlock insights and guide the business in the data domain. This includes everything from advising on technical implementation tradeoffs and priorities (e.g. Storefront’s near real-time or experimentation data capabilities) to developing broad level strategic direction and vision in our customer data strategy and architecting the future data models to meet our users needs and anticipating impactful use cases. All while maintaining data quality and analytical rigor. To be successful, this role requires a blend of analytical experience, strong technical capability, ability to develop and influence business strategy, and stakeholder management; all applied to drive the quality, impactfulness, and vision of  Wayfair’s customer data. 

What You'll Do

• Define and own the strategic agenda to unlock insights and guide the business
• Run open-ended exploratory data analysis to identify new ideas and opportunities
• Consult on A/B tests of our latest technology being implemented (e.g. decoupled services, enhanced recommendations algorithms, new features) to ensure effective and accurate data capture for experimentation reporting
• Proactively monitor our data models to identify potential issues, determine root causes, and resolve. 
• Build new tools that allow us to be more productive and efficient
• Work closely and build productive relationships with our product, engineering and machine learning stakeholders.
• Proactively identify areas where advanced analytical efforts can produce a strong value add and work them into the road map.
• 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.
• 4+ years work experience in a relevant field (in addition to any graduate education).
• Analytics or Data Science experience with e-commerce companies is a strong plus.
• In-depth experience with SQL (aggregate functions, query optimization, stored procedures, string parsing, Vertica/Hive/Presto/Spark, etc.), required.
• In-depth experience with python & python tools (Jupyter notebooks, functions, pandas, sklearn, matplotlib, etc.), required.
• Experience with experimental design (A/B tests) and statistical analysis to drive business decision making, highly preferred. 
• Knowledge and experience using machine learning algorithms/techniques (decision trees, random forest, deep learning, etc.) within a business context, highly preferred. 
• Strong written and verbal communication with a team player, highly collaborative attitude. 
• Ability to collaborate and proactively communicate with stakeholders.
• Proven track record of taking ownership and driving results. Thrive in a fast-paced environment. 
• Strong business acumen, analytical skills, and technical abilities along with problem-solving skills.
• Demonstrated success influencing senior level stakeholders on strategic direction based on recommendations backed by in-depth analysis.
• Prior experience proactively identifying areas where analytical efforts can produce a strong business value add and setting the analytics roadmap.
• Able to manage multiple projects and deliver against aggressive goals.