Revenue and Cost Analytics Manager

INSEAD is seeking a Revenue & Cost Analytics Manager, to join our Executive Education Department. This is a full-time, permanent position based at one of our campuses:

• Middle East Campus in Abu Dhabi, Emirates
• Asia Campus in Singapore

A hybrid working model is in place – 3 days on campus, 2 days from home. The Executive Education department at INSEAD delivers tailored programs for executives and organizations, focusing on leadership development and business innovation. It provides cutting-edge learning experiences that equip professionals with the skills to drive transformation and succeed in a global environment.

About the job 
Provide advanced financial, commercial, and operational analysis that supports strategic decisions across revenue, cost, margin, Sales Operations, and programme economics. Build scalable analytical models and automate recurring analysis and reporting.

Your role within the team

1. Commercial & Management Analytics

• Translate ambiguous management questions into structured analytical approaches, models, scenarios and recommendations.
• Provide decision-oriented analysis to leadership on revenue, cost, contribution and margin performance.
• Present complex findings clearly, highlighting implications, risks, trade-offs and recommended actions.
• Respond to ad hoc business questions while building reusable analytical approaches where possible.

2. Programme Revenue, Cost & Margin Analysis

• Develop programme-level analysis of revenue, cost, contribution and expected margin.
• Identify the main drivers of programme profitability, cost pressure and margin erosion.
• Compare actual and forecast performance against approved assumptions, targets and prior expectations.
• Support programme and business teams in understanding and addressing material performance variances.

3. Forecasting, Scenario Modelling & Cost Standards

• Support revenue, cost and margin forecasting through scenario, sensitivity and trend analysis.
• Build and maintain cost-envelope models and standard cost assumptions for different programme formats.
• Test the financial impact of changes in participant volumes, pricing, delivery models, faculty, travel, venues and other key variables.
• Maintain transparent assumptions and ensure models are updated as business conditions and operating practices change.

4. Commercial, Scheduling & Operational Performance Analytics

• Analyse order-to-cash performance, revenue leakage, cost drivers, operational exceptions and margin erosion.
• Analyse scheduling demand, room and resource utilisation, capacity constraints, provisional holds, cancellations and release patterns.
• Provide insight on scheduling trade-offs and opportunities to improve utilisation, programme placement and operational planning.
• Provide commercial and performance analytics to Sales Operations, Revenue Operations, Cost Operations and leadership.

5. Data, Automation & Analytical Controls

• Automate recurring data preparation, reconciliation, modelling, dashboards and management reporting.
• Establish reliable data definitions, calculation methods and analytical controls.
• Maintain clear documentation of assumptions, source data, methodology and known limitations.
• Work with Data, IT, Finance and operational teams to improve data quality, reporting efficiency and analytical scalability.

The ideal candidate profile

• Bachelor’s degree in Finance, Economics, Business, Engineering, Statistics, Data Analytics, Operations Research or a related quantitative field.

• A postgraduate qualification in Business, Finance, Analytics, Economics or a related discipline would be advantageous.

• Relevant professional certification in financial analysis, data analytics, business intelligence or process improvement would also be beneficial.

• Typically 7–10 years of experience in commercial analytics, business analytics, revenue operations, financial analysis, business intelligence or operational performance.

• Demonstrated experience developing revenue, cost, margin, forecasting and scenario models.

• Experience translating complex or ambiguous business questions into structured analysis and actionable recommendations.

• Experience automating recurring reporting, dashboards, data preparation or analytical

• Growth mindset, collaborative and client focus