About This Role
This is an operational analytics role within a growing local logistics firm, not a tech-heavy data science position. The job involves untangling data from multiple departments—operations, finance, customer service—to produce unified performance reports. It suits someone who enjoys detective work: finding errors in spreadsheets, tracing service failures, and turning messy data into clear business insights for decision-makers.
What the Requirements Say About This Role
The employer is looking for a hands-on auditor and synthesizer, not just a number-cruncher. The emphasis on manual data entry auditing and root-cause investigation suggests they need someone who is detail-oriented and can spot inconsistencies across systems. The 3-5 year experience requirement signals they want a self-starter who can work independently with mid-level autonomy, likely reporting to a manager who expects polished, reliable reports.
How to Approach This Application
Focus your application on examples where you cleaned messy data or reconciled conflicting information from multiple sources. Highlight any experience with logistics metrics like volume, weight, or revenue tracking. The employer will prioritize your ability to catch errors and explain trends clearly—so mention how you’ve previously improved reporting accuracy or helped a team understand operational bottlenecks. Avoid heavy technical jargon about machine learning or advanced modeling.
Who This Role Suits
This role is best suited for a mid-career analyst who enjoys operational problem-solving and can thrive in a fast-growing company where processes are still being built. It is likely moderately competitive, as the logistics sector in Addis Ababa values practical data skills over academic credentials.
Ahununu Trading PLC, a fast-growing logistics company, is looking for qualified and motivated candidates to join our team.
Job Summary
We are looking for a motivated and experianced Data Analyst to join our team.
Duties and Responsibilities
- Consolidate data from RCTO, AOD, Finance, Marketing, Call Center, and other departments into unified Weekly and Monthly Company Performance Reports.
- Track and analyze key operational metrics Volume, Revenue, Weight, and Expenses, sales, financial, customer service, and HR-related data to identify trends and operational bottlenecks.
- Audit manually entered data spreadsheets across departments to identify and correct errors before inclusion in official reports.
- Investigate the root causes of service failures and operational exceptions and develop standardized checklists to prevent recurrence.
- Prepare and maintain the Executive Scorecard, covering the Commercial Pillar (Volume vs. Revenue vs. Weight), Financial Pillar (Departmental Expenses vs. Target Budgets), Operational Health (Exceptions Logged vs. Resolved), and Customer Satisfaction (Service Failures vs. System Improvements).
- Flag early warning signs such as drops in operational volume or spikes in expenses — to enable proactive management decisions rather than reactive responses.
- Support leadership with clear, formula-driven data analysis to guide decisions on cost reduction, failure prevention, and growth planning.
- Maintain data integrity and consistency across departmental reporting templates, ensuring a single, verified source of truth for company performance.
- Perform other data tracking, auditing, or quality control tasks as assigned by the Talent & Corporate Service Department or relevant supervisor.
- Education and qualification: BA in a Business field (Management, Economics, Business Administration, Logistics, or related)
- Experience: Minimum 4 years in data tracking, auditing, or a related analytical role
- Skills: Proficiency in MS Word, Excel, and PowerPoint; comfort with Excel/Google Sheets-based reporting (no new software licenses required)
How To Apply
Interested applicants should send their CV and relevant documents to:
📧 ahununujobs@gmail.com
⏰ Application Deadline: July 25, 2026
📞 Contact (HR): 0970005656
⚠️ Only shortlisted candidates will be contacted.
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