Commercial & Operations Data Analyst

September 10, 2026

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Employer
  • Location: Dubai, Sheikh Zayed Road
  • Experience Required: 4 Year
  • Gender Preference: Any
  • Reference Id: VRBC-JOB-008851

Job Description

Role Purpose

We are looking for a commercially minded Commercial & Operations Data Analyst to support management with clear, accurate analysis of business performance across a multi-location service business.

This is not simply a reporting or dashboard role.

The analyst will be expected to help management understand:

  • What happened
  • What is driving the result
  • Where management should investigate further

The role will work closely with Operations and senior management.

The analyst identifies and quantifies business issues through data.

Operational management owns the decisions and execution.

Key Responsibilities

  1. Commercial Performance Analysis

Analyse performance across brands, locations and service categories, including:

  • Revenue
  • Transactions
  • Average transaction value
  • Service revenue
  • Retail revenue
  • Discounts
  • Service mix
  • Packages and redemptions
  • Actual vs target
  • Month-to-date performance
  • Year-to-date performance
  • Year-on-year performance

Identify the main drivers behind changes in performance rather than simply reporting variances.

For example:

“Transactions are down” is a result.

The analyst should investigate what is driving the decline.

  1. Operational Analysis

Analyse how effectively available labour and capacity are being converted into transactions and revenue.

This includes:

  • Staff working hours
  • Bookable hours
  • Booked hours
  • Utilisation
  • Productivity
  • Booking patterns by hour
  • Booking patterns by day
  • Peak and off-peak demand
  • No-shows
  • Cancellations
  • Waitlists
  • Turnaways
  • Appointment availability
  • Skill availability

Identify patterns that may point to:

  • Poor scheduling
  • Capacity shortages
  • Excess capacity
  • Skill gaps
  • Missed booking opportunities
  • Operational inefficiencies

The analyst should highlight where the issue appears to exist and quantify it where possible.

  1. Client Analysis

Analyse client behaviour, including:

  • First-time clients
  • Returning clients
  • Retention
  • Rebooking
  • Frequency
  • Average spend
  • Service mix
  • Client cohorts
  • Retail purchasing behaviour

Identify where client behaviour is changing and where further investigation is required.

  1. Employee Productivity Analysis

Analyse operational performance by therapist, stylist and location, including:

  • Revenue
  • Transactions
  • Revenue per working hour
  • Booked versus available hours
  • Utilisation
  • Service mix
  • Rebooking
  • Retail performance

The objective is to provide management with evidence that can support coaching, scheduling and operational decisions.

The analyst is not responsible for managing employee performance.

  1. Location Performance

Compare performance across locations and identify:

  • Significant variances
  • Emerging trends
  • Strong and weak performance
  • Capacity differences
  • Productivity differences
  • Client behaviour differences
  • Service mix differences

The analyst should help management understand why one location may be performing differently from another.

  1. Reporting and Dashboards

Prepare and maintain clear management reporting.

Responsibilities include:

  • Weekly performance reporting
  • Monthly performance reporting
  • Power BI dashboards
  • Excel analysis
  • Ad-hoc analysis
  • Improving recurring reporting
  • Reducing manual spreadsheet work
  • Maintaining consistent KPI definitions

Reporting should focus management attention on what matters rather than presenting every available metric.

  1. Data Accuracy

Check and reconcile data before presenting findings.

Identify:

  • Incorrect data
  • Missing data
  • Duplicate records
  • Inconsistent KPI definitions
  • Reporting discrepancies
  • System issues affecting reporting

The analyst should raise data-quality issues clearly rather than working around them silently.

Required Experience

  • 2–4 years’ experience in data analysis, business intelligence, commercial analysis or operational reporting
  • Experience working with large datasets
  • Experience producing management reporting
  • Experience investigating business performance
  • Experience presenting findings to non-technical colleagues

Experience in a multi-location business is preferred.

Relevant sectors include:

  • Retail
  • Hospitality
  • Beauty
  • Fitness
  • Healthcare clinics
  • Restaurants
  • Hotels
  • Other appointment-based or service businesses

Technical Skills

Essential

  • Advanced Excel
  • Good Power BI skills
  • Working knowledge of SQL
  • Data cleaning and reconciliation
  • Trend analysis
  • Variance analysis
  • Basic cohort analysis
  • Strong numerical ability

Advantageous

  • Python
  • Forecasting
  • CRM analytics
  • Automated reporting
  • Experience with booking or workforce-management systems

Advanced Python, machine learning and data engineering are not required.

Personal Qualities

Curious

Does not stop at the first explanation.

Analytical

Can break a broad problem into its underlying drivers.

Commercially aware

Understands which findings matter to business performance.

Accurate

Checks and reconciles numbers before presenting conclusions.

Independent

Can investigate an issue without needing every step prescribed.

Clear

Can explain data simply to managers who are not analysts.

Practical

Focuses on analysis that management can use.