Data Analyst II - Marketing & Customer Analytics

Responsibilities

Partner with business stakeholders on customer and marketing analytics, helping answer key business questions and supporting initiatives that improve performance. Interpret data to identify business trends, customer behaviors, and opportunities across acquisition, retention, loyalty, and marketing performance. Support analysis of customer segments, churn, retention, and buying behaviors to generate actionable recommendations. Build, maintain, and improve recurring reporting and dashboards, while identifying the metrics that matter most to the business.

Conduct ad-hoc analyses to evaluate marketing tactics, campaign performance, and customer outcomes. Support test design, measurement, and readouts for A/B testing and other marketing experiments, helping translate results into practical next steps. Improve and automate data preparation and reporting processes so more time can be spent on high-value analysis. Collaborate with Data Engineering and partners across Analytics to improve data quality, standardized definitions, governance, tools, and ways of working.

Manage multiple priorities across projects and communicate progress, tradeoffs, and insights effectively. Present analyses in a clear, interpretable, and practical way that can be shared broadly with both technical and non-technical audiences.

Bachelor's degree in a technical or analytical field such as Statistics, Economics, Finance, Computer Science, Mathematics, Operations Research, Industrial Engineering, Marketing Analytics, or related experience. 5+ years of experience in analytics, business analysis, or a similar role supporting cross-functional stakeholders. Strong SQL skills and experience working with large datasets, including data extraction, transformation, and quality checks. Experience with data visualization and reporting tools such as Tableau, Power BI, or Google Data Studio.

Experience analyzing customer, marketing, or digital performance data to uncover trends and opportunities. Familiarity with marketing channels and external agencies including social, search, display, CRM, and other digital channels. Familiarity with A/B testing methodology, test measurement, and interpreting results to improve marketing outcomes. Comfort working with AI-enabled tools and technologies to accelerate analysis, improve productivity, and support business decision-making, including developing practical methodologies to QA AI-generated outputs and assess their reliability before use.

Strong ability to interpret data and turn it into practical business actions, recommendations, and prioritization decisions. Strong practical business sense, with the ability to balance analytical rigor with real-world tradeoffs and translate insights into decisions that improve customer and business outcomes. Strong communication and collaboration skills, with the ability to act as a bridge among business, analytics, and engineering teams.

Confidence to scrutinize analyses, identify limitations, and communicate where data quality or methodology may affect interpretation. Familiarity with agile ways of working and tools such as Jira, Git Hub, or Confluence is a plus. Please note that you do not need to qualify for all requirements to be considered. We encourage you to apply if you can meet most of the requirements and are comfortable opening a dialog to be considered.

Ability to sit and work at a computer keyboard for extended periods of time. Ability to stoop, kneel, bend at the waist, and reach daily.