Business Analyst - Retail

Logile, Inc.; India; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Logile, Inc. is seeking a data analytics professional to advance advanced analytics and BI engineering across stores and regions.

You will lead RCA efforts, cohort analysis, and predictive modeling to inform decisions and drive revenue and efficiency. Collaborate with Product, Merchandising, Store Ops, and Engineering to transform raw data into actionable insights, build dashboards in Power BI, and support data pipelines.

Qualifications

• Experience with RCA, cohort analysis, and predictive modeling to drive store-level decisions.
• Strong SQL and BI skills to surface store, category, and executive insights.
• Ability to translate raw data into decisions and feature improvements through cross-functional collaboration.

Responsibilities

• Lead RCAs on volatile business shifts and deliver actionable recommendations.
• Apply cohort analysis, funnel tracking, and forecasting to predict peak retail demand.
• Build heuristic and predictive models to uncover opportunities for revenue and efficiency.

Skills

SQL

Power BI

Data analysis

Forecasting

Cross-functional collaboration

Tools

SSIS/SSAS

Data pipelines

Job description

About Logile

Logile is the leading retail labor planning, workforce management, inventory management and store execution provider deployed in thousands of retail locations across North America, Europe, Australia, and Oceania.

Our proven AI, machine-learning technology and industrial engineering accelerate ROI and enable operational excellence with improved performance and empowered employees. Retailers worldwide rely on Logile solutions to boost profitability and competitive advantage by delivering the best service and products at optimal cost.

From labor standards development and modeling to unified forecasting, storewide scheduling, and time and attendance, to inventory management, task management, food safety, and employee self-service - we transform retail operations with a unified store-level solution. Gain the Advantage with The Logic of Retail. One Platform for store planning, scheduling and execution.

For more information, visit www.logile.com

Key Responsibilities

Advanced Analytics & Root-Cause Analysis

• Root-Cause Analysis (RCA): Lead RCAs on volatile business shifts (e.g., sudden sales dips, inventory stockouts, or spikes in returns and shrinkage) and deliver quick-turnaround, actionable recommendations.
• Cohort & Funnel Analysis: Apply cohort analysis, funnel tracking, and statistical forecasting techniques to predict peak seasonal retail demand (holiday, promotional, back-to-school, and other high-volume periods).
• Decision Models: Build heuristic and predictive models to uncover opportunities for incremental revenue and operational efficiency across stores and categories.

BI Engineering & Data Architecture

• Data Visualization: Build and maintain enterprise-level Power BI dashboards using DAX and Power Query to surface store, category, and executive-level insights.
• ETL Pipeline Support: Support the development and ongoing execution of data pipelines using SSIS, SSAS, or modern data orchestration tools.
• Data Quality Assurance: Own SQL views, stored procedures, and data models that feed reporting and analytics, ensuring data validity and consistency.

Collaboration & Stakeholder Management

• Cross-Functional Partnership: Act as a key analytics partner to Product, Merchandising, Store Operations, and Engineering teams, translating raw data into decisions and feature improvements.
• Knowledge Sharing: Support and mentor junior analysts on analytical approach, SQL, and dashboard best practices.

Strategic Business Drive & Domain Analytics

• Revenue & Pricing Optimization: Analyze demand-supply gaps, inventory utilization, and pricing effectiveness across stores, categories, and regions.
• Conversion & Funnel Management: Deep-dive into customer checkout behavior, cart and basket drop-offs, and return or cancellation bottlenecks to drive retention.
• Campaign & Loyalty Analysis: Partner with marketing teams to design, track, and optimize loyalty programs and promotional campaigns.