Manager, Customer Data Analytics & Insights
At a glance
Manager-level Data Analysis & BI role at Rag & Bone. New York · full-time · $120,000–$140,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Keep customer records accurate as they move between Shopify, the CDP and other customer-facing systems
- Shape customer groups and audience plans for marketing, CRM and personalized outreach
- Turn questions from marketing, ecommerce and merchandising into analyses and practical recommendations
- Build reports on customer lifetime value, retention, cohorts and RFM segments
- Use SQL and Python to analyze customer data, maintain warehouse models and support audience activation
What you bring
- At least four years in customer, data or marketing analytics, or a closely related area
- You can query complex datasets with SQL and use Python for analysis and automation
- You have hands-on experience with a CDP and a cloud data warehouse
- You have worked with Shopify or another major ecommerce platform and understand customer, order and product data
- A quantitative bachelor's degree or equivalent experience
Who this fits
This is a hands-on individual-contributor manager role for someone comfortable with SQL, Python, reporting and presenting findings. You’ll work with marketing, CRM, ecommerce, merchandising and leadership. The position is hybrid, with four days each week in the New York office.
From the employer
Manager of Customer Data Analytics & Insights
DEPARTMENT Customer & Digital Insights and Analytics
REPORTS TO Sr. Director, Customer & Digital Insights and Analytics
LOCATION Hybrid; 4 days in office per week
EMPLOYMENT TYPE Full-Time
About the Role
Rag & Bone is seeking a Manager of Customer Data Analytics & Insights to own the analytics and data infrastructure that powers customer understanding across the business. This role will sit at the intersection of data, marketing, and technology, translating raw customer data into actionable insights, building and maintaining audience segmentation, and ensuring our data ecosystem (UCP, CDP, CRM) works together to support personalized, data-driven marketing and business decisions.
This is a hands-on, individual-contributor role reporting to the Sr. Director of Customer & Digital Insights and Analytics. It's a great fit for someone equally comfortable writing SQL and Python, exploring a large dataset, building reports, and presenting findings and recommendations to stakeholders across marketing, ecommerce, and leadership.
Key Responsibilities
Manage the customer data pipeline across Shopify, the CDP (e.g., ActionIQ), and other customer-facing systems, ensuring data accuracy, consistency, and timeliness.
Build, manage, and continuously refine customer segmentation and audience strategies to support marketing, CRM, and personalization initiatives.
Partner with marketing, CRM, ecommerce, and merchandising teams to translate business questions into analytical frameworks and deliver actionable insights.
Design and maintain dashboards and reporting frameworks (e.g., customer lifetime value, retention, cohort analysis, RFM segmentation) to track key customer metrics.
Write and optimize SQL queries to extract, transform, and analyze large datasets from multiple sources.
Query and maintain customer data within our cloud data warehouse (e.g., Snowflake, BigQuery, Databricks, or Oracle), ensuring models are efficient, well-documented, and accessible to downstream teams.
Use Python for data analysis, automation, and modeling (e.g., churn prediction, propensity scoring, clustering).
Manage and optimize the CDP to ensure clean identity resolution, audience activation, and data governance.
Collaborate with CRM/lifecycle marketing teams (using platforms such as Klaviyo) to support campaign targeting, testing, and measurement.
Identify opportunities to improve data quality, structure, and accessibility across teams.
Present findings and recommendations clearly to both technical and non-technical stakeholders, including senior leadership.
Stay current on best practices in customer analytics, data privacy regulations, and marketing technology.
Qualifications
4–6+ years of experience in customer analytics, data analysis, marketing analytics, or a related field.
Proficiency in SQL for querying and manipulating large, complex datasets.
Working proficiency in Python for data analysis and automation (pandas, numpy, or similar libraries).
Hands-on experience with a Customer Data Platform (CDP), such as ActionIQ, Segment, Tealium, or similar.
Experience working with a cloud data warehouse platform such as Snowflake, BigQuery, Databricks, or Oracle.
Experience working with Shopify or another major ecommerce platform, including familiarity with order, customer, and product data structures.
Strong understanding of customer segmentation methodologies (RFM, cohort analysis, LTV modeling, etc.).
Ability to translate ambiguous business questions into structured analyses and clear recommendations.
Excellent communication skills, with the ability to present data insights to both technical and non-technical audiences.
Strong attention to detail and a rigorous approach to data quality and governance.
Bachelor's degree in a quantitative field (Statistics, Data Science, Economics, Computer Science) or equivalent experience.
- The salary for the role is between $120,000 to $140,000 based on candidates experience and expectations.
Preferred Skills
Experience with a CRM/lifecycle marketing platform such as Klaviyo, Braze, or Attentive.
Experience in retail, eCommerce, or DTC environments.
Familiarity with BI/visualization tools (e.g., Looker, Tableau, Power BI).
Experience with A/B testing and experimentation frameworks.
Knowledge of data privacy regulations (GDPR, CCPA) as they relate to customer data.
What Success Looks Like
Marketing and CRM teams have reliable, well-governed customer segments to activate against.
Customer data flows cleanly and consistently across Shopify, the CDP, and downstream tools.
Leadership has clear, timely visibility into customer behavior, retention, and lifetime value trends.
Data-driven recommendations directly inform marketing strategy and customer experience decisions.
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