About the role

The Staff Marketing Data Analyst organizes and analyzes data from various sources to transform marketing data into meaningful insights that influence decision making. This role will be in support of the Marketing org and will inform data driven strategies across customer lifecycle from acquisition through retention. Within this role, the team member will be a valuable analytical partner to marketing stakeholders, use a range of tools and methodologies to generate results which highlight insights and expose opportunities for improvement. The team member must have high-level communication skills and a good understanding for how their analyses will impact the business.

What you’ll do

• Drive analytical decision making on a wide range of marketing initiatives
• Integrate disparate data resources and leverage state of the art analytics best practices to
  deliver actionable insights to marketing partners to maximize marketing’s contribution to the business growth
• Effectively communicate and present results to teammates and business partners
• Work closely with data engineering, marketing, and product to create holistic analytic
  solutions

About you

• 10+ years of experience in data analysis with focus in digital marketing, channel marketing, CRM, or loyalty marketing
• Experience in leading end-to-end data analysis projects and be a thought leader on measurement methodologies, AB test design, data resources and tools in driving business improvements
• Advance knowledge using SQL to create and manipulate datasets from various sources
• Proven ability to synthesize findings into actionable insights that help drive data driven business outcomes
• Demonstrates leadership skills, teaching or mentoring junior analysts
• Strong statistical knowledge and usage to drive business decisions
• Demonstrated experience with business intelligence tools such as Tableau, PowerBI etc.
• Excellent verbal and written communication skills
• Experience with retail/e-commerce companies is a plus
• Bachelor’s Degree in relevant STEM field (Engineering, Economics, Mathematics, Applied Statistics, Computer Science, Finance)