Role Description We currently have an exciting opportunity for a Data Analyst - eCommerce Analytics to join the Tailored Brands Enterprise Analytics team. As Data Analyst – eCommerce Analytics, your primary responsibility will be to extract actionable insights from data to optimize ecommerce performance with insights from site content, promotions, customer behavioral data, marketing strategies, and market data, just to name a few. You will collaborate with ecommerce product management, category management, and site operations teams to drive data-driven decisions. The primary goal is providing insights for the ecommerce and marketing teams to guide, monitor and measure their strategies. What You’ll Do | Key Accountabilities - Data Collection: Partner with operations to track customer actions on the website through Google Tag Manager and Google Analytics. - Data Analysis: Dive deep into customer behavior data in Google Analytics, sales data in Snowflake, and aggregated data in Power BI dashboards to identify trends, patterns, and opportunities to increase conversion, average order value, and traffic. - Reporting: Create clear, concise, and insightful dashboards via Power BI, Looker Studio, and Excel Pivots. - Presentations: Present analyses in a clear, interpretable, and applicable way that can be shared widely, communicating effectively with both technical and non-technical partners. - Collaborate: Partner with data engineering, ecommerce teams, and across analytics to share learnings, align on methodologies and leverage best practices. Qualifications - Bachelor’s degree in statistics, business, merchandising, or a related field is required. - Minimum of 3 years career experience in ecommerce or analytics. - Google Analytics: Proficiency in analyzing data in GA is required. - SQL: Proficiency in querying databases for data extraction is required. - Data Visualization: Experience visualizing insights effectively using Power BI, Tableau or similar tools (Power BI is Preferred). Requirements - Ability to sit and work at a computer keyboard for extended periods of time. - Must utilize visual acuity, speech and hearing, hand and eye coordination and manual dexterity necessary to operate a computer and office equipment. - Hours regularly 40 hours per week, as work dictates, from a remote office location. Benefits - This role is eligible for healthcare including medical, dental and vision. - Retirement savings (401k with a company match). - Income protection programs such as life, accident and disability insurance. - Paid time off for sick leave, vacation, bereavement, jury duty, and holidays. - Wellbeing program. - Commuter, adoption assistance, education assistance, legal services, and employee merchandise discounts. Work-Life Balance - Meeting-Free Fridays (encouraged) | so you can catch up on work and self-development. - Summer Fridays | from Memorial Day to Labor Day so you can enjoy a head-start to the weekend. - Holiday Early Departure | close out early the business day before a company observed holiday. Compensation The starting salary for this position is $70,200 – $110,000. Actual compensation within this range will be determined based on factors such as skills, experience, and qualifications. Over time, and subject to performance, tenure, and evolving responsibilities, total compensation for this role may grow to as much as $146,300. Base pay information is based on market location and may be subject to prevailing wage laws, if applicable.

• Onboard new data stewards to their role and responsibilities. • Partner with stewards to understand business area needs, gather requirements, and align around common standards. • Help stewards create clear, actionable practices for data use and communication. • Participate in and help facilitate steward meetings and workgroup sessions. • Promote the use of the Analytics Marketplace for cataloging organizational metadata. • Educate data stewards, subject matter experts, and business area users on metadata purpose, structure, and management best practices. • Publish and participate in the maintenance of metadata assets in Collibra, including the use of workflow automation. • Develop, maintain and promote cataloging standards. • Assist in creating training materials and teaching courses as part of an enterprise data fluency program. • Collaborate with content creators outside of the DGO to integrate additional topics and courses into the program. • Evaluate program effectiveness through course feedback and make recommendations for improvements. • Collaborate with business partners to identify data quality issues and analyze root causes. • Support remediation efforts and process improvement opportunities. • Monitor and report on data quality metrics and activities. • Identify data quality trends for key data assets, and report findings to stakeholders. • Support the configuration, maintenance, and troubleshooting of the Analytic Marketplace and related workflows. • Coordinate with product vendor account and support teams regarding updates, enhancements, and issue resolution. • Support enhancement request, defect, and task tracking. • Serve as a mentor and subject matter resource, supporting entry and mid-level analysts. • Assume project management and lead engagement role responsibilities with small to medium projects. • Analyze business processes and workflows to understand how data is captured, managed and used. • Document business requirements, and recommend process improvements that enhance data accuracy, usability, and analytic capabilities. • Other duties as assigned.

• Lead the delivery of analytics solutions combining NetSuite data with Oracle Analytics Cloud. • Own client outcomes end-to-end from discovery to go-live. • Mentor junior consultants and coordinate cross-functional teams. • Design performant analytics solutions and translate client requirements into robust data models. • Collaborate with APEX developers and BI stakeholders.

• Define the right problems: Before any analysis, understand what business question it’s answering and what decision it will inform. Push back if the question is flawed. • Data and insights: Define metrics, build reports, run analyses, design experiments, and surface data insights that move your team’s key metrics. • Drive outcomes: Bring recommendations to your counterparts in product, growth, finance or operations, tell them what’s happening and why, and what next steps should be.