Data Analyst Associate

Arabian Private Holdings


Date: 2 weeks ago
City: Riyadh
Contract type: Full time
About the Role
The Data Analyst Associate joins our advisory team to transform raw corporate data into clear, defensible insights for our clients. In this position, you will support critical mandates where finding answers requires analyzing complex holdings and structuring messy corporate databases. Our client is an established regional holding group requiring immediate clarity on its portfolio, and your work will form the analytical foundation for the strategic guidance we deliver.

About Arabian Private Holdings
Arabian Private Holdings was founded on the principle that critical business decisions do not require massive consulting teams or hundreds of pages of presentation slides. We work directly with a select number of family groups, holding companies, and government entities to provide honest, independent advice on governance, corporate strategy, and operating model performance. Because we are a principal-led firm, our associates do not hide behind senior management. You will work directly with our leadership, helping our clients sit with complex problems, form a view, and execute on structural decisions.

What You Will Do
  • Gather and structure operational and financial data from diverse business units across regional holding companies.
  • Build clear, logical data models to support strategic decisions regarding portfolio clarity and asset allocation.
  • Conduct market and industry research to help our principals form a view on new investment paths or regulatory shifts.
  • Analyze corporate governance structures and operating model performance to identify commercial inefficiencies.
  • Prepare clean, precise charts and data summaries that translate complex numerical patterns into straightforward business realities.
  • Maintain our database of regional transaction activity and corporate performance benchmarks to support ongoing mandates.
  • Participate in internal working sessions, presenting your quantitative findings directly to the lead partners.


What We Are Looking For
  • Strong quantitative skills with the competence to clean and analyze unstructured datasets in Excel, SQL, or Python.
  • Exceptional written precision: you write with clarity and avoid academic jargon, marketing speech, or promotional language.
  • Uncompromising logic and a natural curiosity to understand how different business models generate revenue.
  • The ability to organize your thoughts and present structured arguments supported by objective data.
  • A disciplined approach to accuracy, where you routinely double-check your calculations before sharing your work.
  • Comfort working in a self-directed environment, taking ownership of your analytical tasks from start to finish.


How We Work
We operate under a hybrid model that balances focused, independent analysis with structured in-person collaboration. Our team spends part of the week collaborating directly in shared workspaces to review active mandates and mentor junior colleagues, while utilizing remote working days for deep analytical tasks. This combination ensures that you receive direct, principal-led guidance on a daily basis while retaining block time to focus on your analysis. We value directness, intellectual honesty, and respect for your colleagues' time: which means meetings are concise and every team member is expected to speak with clarity.

What the Role Offers
  • A paid position with highly competitive compensation designed for entry-level talent in this market.
  • Direct exposure to senior decision-makers and high-profile regional mandates that legacy consulting firms rarely offer to junior analysts.
  • Structured, one-on-one mentorship from experienced partners who are invested in your analytical development.
  • A hybrid working arrangement that provides the flexibility to work from home alongside focused, in-person collaborative sessions.
  • The opportunity to build a rare foundation in corporate governance, strategy, and operating model evaluation.

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