Sr Data Analyst - Store Analytics

Tailored Brands•Dublin, CA

1d•$106,800 - $145,000•Remote

About The Position

Tailored Brands is a leading specialty retailer of menswear, including suits, formalwear, sportswear, and a broad selection of business casual offerings. Our brands include Men's Wearhouse, Jos. A. Bank, Moores and K&G Fashion Superstore, which offers merchandise for the entire family. We help people love the way they look and feel for their most important moments by delivering personalized products and services through our convenient network of stores and e-commerce sites. We currently have an exciting opportunity for a Sr Data Analyst – Store Analytics, to join the Tailored Brands Enterprise Analytics team. The Sr Data Analyst – Store Analytics serves as a strategic analytics partner to Stores leadership and enterprise leaders, driving deeper understanding of store performance through diagnostic and exploratory analysis. This role goes beyond reporting to identify root causes of business performance, uncover opportunities, develop actionable recommendations, and influence decisions that improve sales, productivity, customer experience, and operational effectiveness. The Sr Analyst independently leads complex analyses, develops scalable analytical frameworks, partners closely with business leaders and Data Engineering, and helps shape the evolution of the Store Insights capability.

Requirements

Bachelor’s degree in Analytics, Statistics, Economics, Mathematics, Business, Information Systems, or a related field; advanced degree a plus.
8+ years of progressive experience in analytics, business intelligence, consulting, retail analytics, or related quantitative disciplines, with demonstrated success solving complex business problems through data.
Demonstrated experience performing diagnostic, root cause, and exploratory analyses that influenced business decisions.
Proven ability to work independently with minimal direction, prioritize competing initiatives, and manage multiple high-impact analytical projects.
Experience presenting analytical findings to senior leadership and influencing cross-functional stakeholders.
Advanced SQL proficiency with experience optimizing complex queries and working with large enterprise datasets.
Strong experience with Power BI, semantic models, DAX, and modern BI best practices.
Working knowledge of Python, statistical analysis, and modern analytics workflows.
Strong attention to detail and demonstrated experience with data validation, KPI governance, and metric consistency.
Ability to synthesize findings into clear written and verbal recommendations for business stakeholders.
Experience working with cross-functional partners to translate business questions into analytical solutions.

Nice To Haves

Experience applying statistical methods, experimentation, forecasting, or predictive techniques is preferred.
Experience in retail, multi-unit operations, consumer analytics, or store performance analytics strongly preferred.

Responsibilities

Lead complex diagnostic and ad hoc analyses that identify root causes of store performance, quantify business opportunities, and guide strategic decision-making across Stores.
Independently frame ambiguous business questions, formulate analytical approaches, synthesize multiple data sources, and translate findings into executive-ready recommendations.
Perform root cause analysis to explain sales trends, labor productivity, conversion, customer behavior, and operational performance, developing hypotheses and validating findings through quantitative analysis.
Proactively identify emerging risks and opportunities across the store fleet by monitoring leading performance indicators and conducting exploratory analyses.
Develop and maintain enterprise Power BI dashboards and analytical solutions that enable leaders to self-serve insights while ensuring metric governance and reporting consistency.
Serve as a key analytics partner in the migration from Tableau to Power BI by leading report validation, metric reconciliation, user acceptance testing, and adoption of standardized reporting.
Partner with Data Engineering and business stakeholders to validate semantic-layer logic, metric definitions, data quality, and reporting consistency.
Drive development of scalable Store Insights capabilities by identifying repeatable analytical opportunities, automating recurring analyses, and advancing self-service analytics.
Present findings and recommendations to senior leaders, influencing business strategy through clear storytelling and data-driven insights.
Support store growth analytics initiatives through data preparation, exploratory analysis, performance tracking, and post-investment measurement for new stores, remodels, and market activations.
Develop repeatable analytics workflows that reduce manual reporting effort and improve the speed, quality, and consistency of insight delivery.
Create executive-ready charts, tables, dashboards, and written summaries that communicate findings clearly to both technical and non-technical audiences.
Apply advanced analytics tools and techniques, including SQL, Power BI, Python, and external data sources, to solve complex business problems and continuously improve analytical capabilities.
Recommend new metrics, analytical approaches, and measurement frameworks that improve how Stores evaluate performance and make decisions.