Career Directions Limited (CDL)

Data Analyst-Revenue&Collections

Career Directions Limited (CDL) Nairobi, Kenya

Staffing and Recruiting · 51-200 employees

Oct 22
data-analyst Mid (2-5 yrs) Full-time Kenya
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About the role

The Data Analyst will monitor and analyze revenue collection, payment patterns, and outstanding balances to identify revenue leakage and improve cash flow. They will also develop performance dashboards and provide actionable insights to management to support portfolio profitability and operational efficiency.

What they look for

Data Analysis Revenue Analytics Financial Reporting Receivables Analysis Excel Google Sheets Power BI Tableau SQL Data Visualization Data Cleaning Data Validation Reconciliation Business Intelligence Problem-solving Communication

Requirements

Candidates must hold a bachelor's degree in a relevant field and possess 2–4 years of experience in data or financial analysis. Proficiency in Excel, SQL, and data visualization tools like Power BI or Tableau is required, along with strong reconciliation and problem-solving skills.

Full description

Role Purpose

The Data Analyst – Revenue & Collections will analyse property, booking, revenue, payment, and operational data to improve revenue performance, strengthen revenue collection, reduce outstanding balances, identify revenue leakage, and improve cash flow. The role will be responsible for tracking collections against amounts billed or due, identifying payment delays and discrepancies, developing collection performance dashboards, and providing actionable insights to management to support timely revenue recovery and portfolio profitability.

Key Responsibilities

1. Revenue Collection & Outstanding Payments

- Monitor and analyse revenue collection across properties, clients, booking channels, and other revenue sources.

- Track amounts billed, amounts collected, outstanding balances, overdue payments, and collection rates.

- Develop and maintain dashboards showing collection performance, ageing of receivables, overdue accounts, and collection trends.

- Identify delayed payments, unpaid invoices, underpayments, and discrepancies between expected and actual collections.

- Work with Finance, Revenue, Operations, and Property Management teams to investigate collection gaps and support timely follow-up on outstanding payments.

- Analyse collection patterns and identify recurring causes of payment delays, arrears, and revenue losses.

- Reconcile booking, billing, payment, and bank or payment-platform data to confirm that revenue due has been received and accurately recorded.

- Monitor collection targets and provide regular reports on collection performance, outstanding balances, and recovery progress.

- Identify revenue leakage, unrecorded income, and discrepancies between bookings, charges, invoices, and payments, recommending corrective action.

- Recommend data-driven measures to improve collection efficiency, reduce overdue balances, and strengthen cash flow.

2. Revenue & Property Performance Analysis

- Analyse property and portfolio performance using occupancy, revenue, Average Daily Rate (ADR), Revenue per Available Room (RevPAR), booking pace, and collection metrics.

- Compare performance across properties, locations, booking channels, and time periods to identify trends and opportunities for improvement.

- Support pricing, forecasting, and revenue management decisions using historical performance and demand data.

- Analyse revenue, costs, profitability, and collection performance to assess the financial contribution of individual properties and the overall portfolio.

3. Reporting & Data Visualization

- Develop and maintain dashboards and weekly and monthly reports covering revenue generated, collections, outstanding balances, arrears, and property performance.

- Translate complex data into clear findings and practical recommendations for management.

- Monitor key performance indicators, including collection rates, overdue balances, receivables ageing, revenue variances, and property profitability.

4. Data Quality, Reconciliation & Automation

- Clean, validate, and reconcile data from Property Management Systems (PMS), online travel agencies (OTAs), payment platforms, accounting systems, and spreadsheets.

- Investigate and resolve discrepancies between bookings, invoices, expected revenue, and actual payments.

- Automate recurring reports and data preparation processes to improve accuracy and reduce manual work.

- Collaborate with Finance, Revenue, Operations, and Property Management teams to maintain accurate and consistent records.

Requirements

Qualifications & Experience

- Bachelor’s degree in Data Analytics, Business Analytics, Data Science, Finance, Accounting, or a related field.

- At least 2–4 years of experience in data analysis, revenue analytics, business intelligence, financial reporting, or receivables analysis.

- Demonstrable experience tracking revenue collections, reconciling payments, analysing outstanding balances, and monitoring overdue accounts is essential.

- Proven ability to analyse collection performance, identify revenue discrepancies, and provide insights that support improved collection rates and cash flow.

- Advanced proficiency in Excel or Google Sheets, including PivotTables and XLOOKUP.

- Experience using Power BI, Tableau, or a similar data visualization tool.

- Working knowledge of SQL for data querying and analysis.

- Strong skills in data cleaning, validation, reconciliation, and reporting.

- Strong analytical and problem-solving abilities, with the capacity to turn data into actionable business recommendations.

- High attention to detail and strong communication skills, including the ability to present findings to technical and non-technical stakeholders.

Added Advantage

- Experience in short-term rentals, serviced apartments, hotels, property management, or real estate.

- Familiarity with Airbnb, Booking.com, Property Management Systems (PMS), payment platforms, or accounting systems.

- Experience analysing accounts receivable, payment ageing, collection efficiency, and revenue leakage.

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