Business Analyst ( Retail Operations & AI Integration )

Role Overview

We are seeking a data-driven and forward-thinking Business Analyst to join our retail team. In this role, you will bridge the gap between complex retail data and strategic decision-making. Your primary focus will be transforming raw retail datasets into actionable business insights through thorough analysis, rigorous report preparation, and high-impact presentations.

A critical expectation of this role is the delivery and presentation of structured insights at regular, recurring intervals to ensure leadership is constantly aligned. Additionally, as part of our digital transformation, this role requires proactive familiarisation, practice, and adoption of modern AI productivity tools to enhance analytical speed and automate these reporting workflows.

As a core collaborator working directly with our multiple functional teams, this is a 100% full-time, working-from-office role based at our corporate headquarters.

Key Responsibilities

Data Analysis & Insights

· Perform quantitative analysis on historical sales, customer purchase patterns and other defined Metrics.

· Identify operational inefficiencies, bottlenecks, or margin leakage across multiple channels.

· Leverage predictive analytics and statistical forecasting techniques to project consumer trends and demand patterns.

Report Preparation & AI Automation

· Design, build, and maintain Daily, Weekly, and Monthly retail performance reports covering key metrics like Same-Store Sales (SSS), and footfall conversion.

· Dedicate regular practice hours to testing AI tools (e.g., ChatGPT Advanced Data Analysis, Microsoft Copilot, or specialized retail forecasting AI platforms) to streamline, speed up, and automate routine reporting tasks.

· Monitor data integrity closely by vetting raw data source systems (POS, ERP, and CRM platforms) to minimize reporting discrepancies.

Regular Presentation & Stakeholder Communication

· Present business summaries and projections at fixed intervals, managing a rigid presentation cadence:
• Daily: Highlight flash sales anomalies or sudden performance spikes to store operations.
• Weekly: Present consolidated performance decks during weekly meetings to guide and take appropriate actions.
• Monthly: Deliver narrative-driven performance reviews and quarterly forecasts to Sales leadership.

· Translate complex data findings into clean, visually engaging executive dashboards and slide decks.

· Utilize AI-driven visualisation aids and design frameworks to build clear, narrative-driven recommendations that explain why trends are happening, rather than just stating what the data is.

Work Environment & Schedule

· Job Type: Full-time, Permanent

· Location: Corporate Office (Fully Working From Office)

Requirements

Required Skills & Qualifications

Technical & AI Competencies

· AI Tool Proficiency & Practice: Practical familiarity with Large Language Models (LLMs) and Generative AI platforms (e.g., ChatGPT, Claude, Microsoft Copilot). Candidates must demonstrate the ability to construct effective prompts for data analysis, code generation (SQL/Python), and report text summarization.

· Advanced Excel Skills: Mastery of Pivot Tables, VLOOKUP/XLOOKUP, nested formulas, Power Query, and data modelling.

· Data Visualization Tools: High proficiency in building dashboards.

· Database Skills: Foundational ability to write queries to extract data directly from retail databases.

· Retail Acumen: Prior understanding of standard retail KPIs (e.g., sell-through rates, inventory aging, average transaction value) is highly preferred.

Professional & Interpersonal Skills

· Presentation Skills & Punctuality: Proven ability to stand up, present clearly, and hit strict, recurring deadlines for business reviews without delays.

· Adaptability & Continuous Learning: A strong mindset geared toward continuous practice, self-paced learning, and adaptation to new software, tools, and platforms.

· Exceptional Communication: Strong command of verbal and written English, with an innate ability to explain technical and AI-generated findings to non-technical store managers or commercial leads.

· High Attention to Detail: Critical mindset to spot calculation anomalies or AI-generated inaccuracies before reporting.

Education & Experience

· Degree: Bachelor's degree in Business Administration, Finance, Economics, Statistics, or a closely related field.

· Experience: 2 to 4 years of proven experience as a Business Analyst or Data Analyst—ideally within a retail, FMCG, or e-commerce setting. Candidates who have actively managed recurring reporting cadences and experimented with AI tools will be given strong preference.

Benefits

PF
Overtime Allowance
Health Insurance