Business Analyst ( Retail Operations & AI Integration )

Role Overview

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