Customer Engagement Data Analyst

Adore Me, a subsidiary of Victoria’s Secret & Co. (NYSE: VSXY) since being acquired in December 2022, is looking for a hands-on Data Analyst who combines strong technical skills with business judgment to improve customer engagement, and maximize lifetime value across CRM, loyalty programs and retention initiatives.

You will own analyses from business questions through data extraction, SQL data analysis, to business recommendations. You will partner with cross-functional teams to help prioritize projects, drive action, measure results and suggest next steps to maximize impact.

Responsibilities:

• Write complex SQL queries to analyze our customer file in depth: customer cohorts, purchase journeys, reachability, and engagement patterns to explain performance changes and identify opportunities to improve retention, repeat purchases, and lifetime value.
• Build automated reporting and measure incremental impact across CRM channels (email, SMS, push), and loyalty programs. Define consistent KPIs, design and analyze A/B tests and holdout experiments to guide targeting, messaging content and frequency, and lifecycle timing.
• Develop customer segments and analytical models using purchase behavior, product affinities, category preferences, RFM, and engagement signals to support personalization, cross-selling, reactivation, and LTV forecasting.
• Partner with Data Engineering and Business Intelligence to ensure data is accurate, reliable, and actionable, aligning on definitions, addressing data gaps, and improving analytical datasets.
• Drive business impact by identifying growth opportunities, guiding projects’ prioritization based on expected revenue, retention, and profitability impact. Partner with stakeholders implementing the recommendations to measure outcomes and recommend which initiatives to scale, refine, or discontinue.

Minimum Qualifications:

• 2 years of hands-on SQL experience, regularly writing complex queries independently. Strong command of CTEs, window functions, multi-table joins, conditional aggregations, and query optimization in BigQuery, Snowflake, or a comparable warehouse.
• Ability to translate an ambiguous business question into an analytical approach, explore unfamiliar datasets, and deliver reliable, actionable findings.
• Strong understanding of data granularity, deduplication, and join logic, with the rigor to validate results and prevent misleading conclusions.
• Experience building dashboards in Looker, Looker Studio, Tableau, or Power BI.
• Solid quantitative skills, including cohort analysis, customer metrics, and statistical interpretation of experiments.
• Strong business judgment: understand how customer behavior drives revenue and profitability, connect detailed findings to the bigger picture, and focus on opportunities that materially improve performance.
• Ownership and a bias for action: take initiative, move work forward independently, and follow through from identifying a problem to helping implement a solution.
• Ability to communicate findings clearly and balance attention to detail with timely, practical decision-making.
• Ability and willingness to work on-site at our office in Tribeca 3 days per week

Preferred Qualifications:

• Python or R for deeper analysis, automation, or predictive modeling.
• Experience with CRM and loyalty data, customer segmentation, LTV forecasting, or churn modeling.
• Familiarity with e-commerce business models and incrementality measurement.
• Degree in Data Analytics, Statistics, or a related quantitative field.