Data Scientist II

At their core, the Customer Tech Data Science team at Wayfair is strong in quantitative analysis and enjoys coding but also wants to balance that with their interest in business and applying advanced modeling techniques. They think critically to tackle complex challenges, thrive in a fast-paced environment and are seeking a high-growth opportunity where they will have an immediate impact on day one. There are significant opportunities for new team members to emerge as leaders, taking on additional projects and responsibilities with strong performance.

Responsibilities:

• As a Data Scientist, you'll play a critical role in uncovering insights that shape strategic decisions and improve business performance.
• Construct optimized code that processes information from multi-terabyte data sources, including sales, clickstream, logistics, product, and customer databases, to deliver business insights and recommendations.
• Collaborate with all facets of the organization, including product management, engineering, and creative design, to identify the most impactful ways for data and analytics to drive decision-making and accelerate profitable growth.
• Become the subject matter expert for data, analytics, and testing for your area to ensure accurate and proper interpretation of core business metrics and consumer behavior.
• Design, execute, and analyze A/B tests to make high-impact changes to the customer experience.
• Perform deep-dive analysis, including the application of advanced analytical techniques, to solve some of the more critical and complex business problems.
• Build, automate, and maintain scalable dashboards and reports using tools like Looker, BigQuery (GBQ), SQL and Python to enable efficient and self-serve data access for stakeholders.

Requirements:

• Bachelor's in Computer Science, Computer Engineering, Analytics, Mathematics, Statistics, Information Systems, Economics, or other quantitative disciplines; a Master's is preferred.
• 3 - 5 years of work experience in a relevant field, such as analytics or data science.
• Proficient knowledge of a statistical programming language such as Python, R, SAS, or SPSS.
• Proficient knowledge of SQL (incl. Aggregate functions, joins, etc. ).
• Experience conducting quantitative analyses on large and complex data sets.
• Experience in leveraging modeling algorithms to derive business insights.
• Experience with experimental test design such as A/B testing.
• Experience with experimental design (A/B tests) and statistical analysis to drive business decision-making, required.
• Experience with data visualization software (e. g., Google Data Studio, Tableau, Power BI); experience with Looker a plus.
• Analytical, creative, and innovative approach to solving problems.
• Strong written and verbal communication.
• Ecommerce or retail analytics experience is a plus.