Role Purpose:
The Data Analyst: Finance Business Partnering is responsible for sourcing, integrating, validating and analysing financial, commercial and operational data from key Eduvos systems and departments to support decision-making, forecasting and performance management. The role extracts and consolidates data from Microsoft Dynamics 365 Finance and Operations, Dynamics 365 Customer Engagement, Microsoft Fabric and other relevant platforms to create monthly models, dashboards and analysis for the Head of Finance, the Senior Manager: FP&A and Finance Business Partners. The role supports budgeting, modular-level revenue forecasting, debt and collections analysis, staffing utilisation modelling, gross profit margin calculations, scenario modelling and resource planning, ensuring insights are accurate, timely and commercially actionable.
Qualifications / Education / Certification:
- Relevant Bachelor's degree in Finance, Accounting, Data Analytics, Data Science, Information Systems, Computer Science, Statistics, Economics, Business Science or a related field.
- Relevant Microsoft certification in Power BI, Fabric, Azure Data, Dynamics 365 or Data Analyst Associate is advantageous.
- A postgraduate qualification or finance/analytics certification would be advantageous.
Experience:
- Minimum of 3-5 years of experience in data analysis, financial analysis, FP&A, business intelligence or a similar analytical role. Experience in budgeting, forecasting, revenue modelling, debtor/collections analysis, gross profit margin calculations, staffing utilisation, ERP/CRM data, Power BI and Microsoft Dynamics 365 Finance and Operations, CE (Sales Hub) or Microsoft Fabric would be advantageous.
Data Sourcing, Integration and Controls:
- Source data from Microsoft Dynamics 365 Finance and Operations, CE (Sales Hub), Microsoft Fabric and approved departmental systems, as well as incorporate external market data.
- Consolidate, transform and reconcile data into structured datasets for finance modelling, reporting, budgeting and forecasting.
- Maintain documented data sources, definitions, assumptions and reconciliation controls.
Monthly Analysis, Modelling and Reporting:
- Prepare monthly models, dashboards and analysis covering revenue, enrolments, cancellations, pipeline, pricing, debt and collections, staffing utilisation, gross profit margins, cost drivers and other performance metrics.
- Analyse trends, variances and relationships to explain performance and identify risks or opportunities.
- Convert data outputs into clear, practical insights for finance and non-finance stakeholders.
Budgeting and Modular Revenue Forecasting:
- Support the annual budget, rolling forecast and reforecast processes at module, qualification, faculty, campus, intake and other relevant levels.
- Build revenue forecasts using student volumes, module registrations, pricing, discounts, cancellations, pipeline, academic calendar, collections and gross profit margin assumptions.
- Develop scenario models to support strategic and operational decision-making.
- Predictive Modelling: using statistical methods or machine learning to predict student churn (cancellations) or collection probabilities.
Commercial Finance Modelling - Debt, Collections, Utilisation and Gross Profit Margins:
- Build and maintain debt and collections models covering debtor ageing, collection rates, payment behaviour, cancellation risk and cash-flow indicators.
- Model staffing utilisation, workload, FTE utilisation, contact hours, student-to-staff ratios, capacity and productivity indicators to support resource planning.
- Calculate gross profit and gross profit margins at module, qualification, faculty, campus, intake and other relevant levels using approved revenue, discount, direct cost and staffing/resource assumptions.
Resource Planning and Capacity Analytics:
- Develop analysis to support lecturer/resource planning, workload, staffing utilisation, student-to-staff ratios, module demand, campus/classroom capacity and support function requirements.
- Link resource assumptions to student growth, modular demand, service levels, utilisation levels, cost-to-serve and financial impact.
- Identify capacity risks, resourcing gaps, utilisation pressure points and cost implications early.
Stakeholder Collaboration and Business Partnering:
- Work with the Head of Finance, Senior Manager: FP&A, Finance Business Partners and departmental stakeholders to understand requirements and translate them into data outputs.
- Facilitate data input, assumptions gathering and model review sessions for budgets, forecasts and monthly analysis.
- Communicate technical findings in a concise, business-focused way.
Continuous Improvement, Automation, Governance and Security:
- Identify opportunities to automate recurring reporting and reduce manual effort using Power BI, Excel, SQL, Fabric or other approved tools.
- Participate in requirements gathering, testing and implementation of data and reporting enhancements.
- Support data quality management and handle sensitive information in line with Eduvos policies and access controls.
Functional competencies:
- Advanced Excel and financial modelling capability.
- Power BI dashboard/report development and datavisualisationskills.
- SQL/querying/data extraction skills; ability to work with Microsoft Fabric, dataflows, datawarehousesor equivalent tools.
- Working knowledge of Dynamics 365 Finance and Operations, CE (Sales Hub)and related finance/operational systems.
- Understanding ofbudgeting, forecasting, revenue modelling, varianceanalysis and performance reporting.
- Commercial finance modelling skills, including debtor andcollectionsanalysis, staffing utilisation, capacity modelling, gross profit and gross profit margin calculations.
- Ability to reconcile data across ERP, CRM, BI and departmental systems.
- Strong analytical, critical thinking and problem-solving skills.
- Ability to document assumptions, data definitions, calculation methodologies,workflowsand controls.
- Ability to communicate complex insights clearly to finance and non-finance stakeholders.
- Strong planning,prioritisationand time management.
Behavioural competencies:
- Initiative and accountability
- Constructive teamwork and collaboration
- Business partnering mindset
- Effective communication and stakeholder influence
- Technical curiosity and continuous improvement
- Analysis and judgement / problem solving
- Time management and systematic approach (planning andorganising)
- Execution - attention to detail
- Confidentiality and ethical handling of data– strong POPIA compliance
- Steadiness under pressure and deadlines
- Conflict Resolution and Negotiation
