URBN - Lead Data Analyst

URBN; Philadelphia (Philadelphia County); On-site; USD 110,000 - 160,000; Full time

Job summary

URBN's Data Science & Analytics team is seeking a Lead Data Analyst to drive complex analytical work, provide technical leadership, and partner across the business. You'll start by focusing on Inventory Science, collaborating with Supply Chain, Merchandising/Planning, Data Scientists, and ML Engineers to improve inventory and fulfillment decisions.

This hands-on role blends SQL and analytical expertise with business curiosity, bridging data across systems, validating results, and translating

Qualifications

• 5+ years of analytics or quantitative work with ownership of analyses.
• Advanced SQL with performance optimization and data validation.
• Proficiency in Python for analysis (pandas).
• Experience building analytical datasets and data models in a modern data warehouse environment (e.g., Snowflake, BigQuery, Redshift).
• Strong analytical problem-solving skills, including identifying biases and navigating ambiguous questions.
• Experience collaborating with Data Engineering to investigate data quality issues.
• Demonstrated ability to mentor peers and promote analytical best practices.
• Strong communication skills to translate complex findings for technical and business stakeholders.
• Experience using AI-powered analytical or coding tools with validation and judgment.

Responsibilities

• Develop a deep understanding of data across source systems, investigating discrepancies and tracing issues to root causes.
• Build analytical datasets and data models to support advanced analysis, experimentation, and data science initiatives.
• Partner with Data Engineering to define analytical data requirements and address upstream data quality issues.
• Develop measurement frameworks and design experiments, holdouts, and other approaches to evaluate business initiatives and data science solutions.
• Develop dashboards and self-service reporting in Looker and Qlik, and document metrics, methodologies, and data lineage.
• Lead complex analytical initiatives, translating ambiguous business questions into actionable insights and recommendations.
• Partner with business and Technology stakeholders to identify opportunities, quantify potential impact, and define metrics for success.
• Collaborate with Data Scientists, ML Engineers, and business partners to frame problems and communicate findings.

Skills

Advanced SQL

Python (pandas)

Data modeling

Data quality investigation

Mentoring teammates

Business storytelling

Statistical analysis

Cross-functional partnership

Problem solving

Tools

Looker

Qlik

Snowflake

BigQuery

Redshift

Job description

Role Summary

URBN's Data Science & Analytics team partners with our brands and shared-service teams to turn data into better decisions, from customer insights to advanced analytical solutions. As we expand our analytics capabilities, we're looking for a Lead Data Analyst to drive complex analytical work, provide technical leadership, and serve as a trusted analytics partner across the business.

You'll initially focus on Inventory Science, partnering with Supply Chain, Merchandising/Planning, Data Scientists, and ML Engineers to improve inventory and fulfillment decisions.

Over time, your scope will broaden to support analytical initiatives across URBN's brands and Technology teams, including areas such as marketing, customer analytics, search, and personalization.

This is a hands-on technical leadership role with potential to grow into people leadership as the team expands.

This role blends deep SQL and analytical expertise with genuine curiosity about how the business operates. You're comfortable working well beneath the dashboard - reconciling data across systems, tracing outcomes to their root causes, and connecting analytical findings to what's happening in the business.

You enjoy tackling ambiguous problems, proactively identifying opportunities, and helping others strengthen their analytical skills.

Role Responsibilities

Data Foundations & Analytical Enablement

Develop a deep understanding of data across source systems, investigating discrepancies, validating accuracy, and tracing issues to their root causes.

Build analytical datasets and data models to support advanced analysis, experimentation, and data science initiatives.

Partner with Data Engineering to define analytical data requirements and address upstream data quality issues.

Develop measurement frameworks and design experiments, holdouts, and other approaches to evaluate business initiatives and data science solutions.

Develop dashboards and self-service reporting in Qlik and Looker, and document key metrics, methodologies, and data lineage to ensure consistency and reliability.

Advanced Analytics & Business Partnership

Lead complex analytical initiatives, translating ambiguous business questions into actionable insights and recommendations.

Partner with business and Technology stakeholders to identify opportunities, quantify potential impact, and define metrics for success.

Collaborate with Data Scientists, ML Engineers, and business partners to frame problems, establish analytical requirements, and communicate findings that drive decisions.

Translate complex analyses into compelling data stories, clearly communicating key insights, business implications, and actionable recommendations to stakeholders.

Technical Leadership & Mentorship

Serve as a technical lead for advanced analytics work, guiding analytical approaches and ensuring high-quality, defensible results.

Establish and promote best practices for SQL, code quality, analytical rigor, validation, and documentation.

Mentor analysts through technical guidance, code reviews, and collaborative problem-solving, helping elevate the team's analytical capabilities.

Initial Focus: Inventory Science

The initial focus of this role will be supporting inventory and fulfillment optimization initiatives across URBN's brands, including purchase order splitting, retail store allocation, and order sourcing.

Size and prioritize opportunities, quantifying current-state costs and potential improvements in dollars, units, service levels, and labor.

Define and own performance metrics, such as sell-through, fill rate, split shipment rate, and cost-to-serve, and evaluate the impact of new optimization solutions.

Translate operational and merchandising constraints into analytical requirements and investigate unexpected outcomes to support model development and improvement.

Role Qualifications

Must-Have

• 5+ years of experience in analytics or quantitative roles, with demonstrated ownership of complex analyses that influenced business decisions.
• Advanced SQL skills, including complex queries, performance optimization, and data validation.
• Proficiency in Python for analysis, including pandas and standard analytical libraries.
• Experience developing analytical datasets and data models in a modern data warehouse environment (e.g., Snowflake, BigQuery, Redshift).
• Strong analytical problem-solving skills, including statistical analysis, the ability to identify and mitigate potential biases, and independently navigate ambiguous business questions.
• Experience working across source systems and collaborating with Data Engineering to investigate data quality issues.
• Demonstrated ability to provide technical guidance, mentor peers, and promote analytical best practices.
• Strong communication skills, with the ability to translate complex findings for both technical and business stakeholders.
• Experience using AI-powered analytical or coding tools with appropriate validation and judgment.

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