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Lead Data Analyst 

About the Organization Winc  


As a Lead Analyst, you will play a pivotal role in the growth and success of Winc. You will lead analytic initiatives that inform our most critical business decisions and develop strategic insights to further the use of analytics as a value driver across our organization. Executives and senior leadership heavily rely on the Analytics team to solve challenging problems and make actionable recommendations based on data. The right person for this role thrives in a fast-paced environment and is motivated by a highly visible and impactful position.



  • Be a strategic advisor for the business, identifying high-impact analytical problems, and finding innovative solutions with data

  • Lead initiatives that define KPIs and diagnostic metrics in close partnership with cross-functional teams (primarily acquisition, engagement & retention, and brand)

  • Translate business requirements into technical specifications and explain complex analysis through informative and well-organized presentations

  • Build data models, data visualizations, and operational analytics that communicate insights across the organization

  • Construct data pipelines to enable business users with self-service tools

  • Champion hypothesis-driven approaches to statistical analyses in order to guide experiments across marketing and digital product functions


Exempt/Non-Exempt Exempt  
Full-Time/Part-Time Full-Time  
Position Requirements


  • 5+ years of experience translating ambiguous business problems into informative insights through hands-on analysis

  • 5+ years of experience building performant dashboards using Tableau, Domo, or similar software - with proficiency in designing clean crisp visualizations

  • 4+ years experience writing robust performant SQL, proficiency with Python and/or R

  • 2+ years experience with A/B testing and basic statistical analysis

  • Excellent communication skills, with the ability to deliver complicated findings and explain technical approaches to a variety of audiences

  • An understanding of data warehousing and ETL concepts including data pipelines, data quality, and business logic

  • An aptitude to proactively identify gaps in data infrastructure, evaluate potential solutions, and coordinate across teams to address issues


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