Revenue Manager

Role: Revenue Manager
Contract Type: Permanent
Location: Marylebone Station, London
Salary: Up to £44,000 per annum

Job Purpose
The Revenue Manager leads Chiltern Railways’ revenue performance function, overseeing monitoring, forecasting, budgeting, analysis, and reporting. The role transforms complex commercial, operational, and customer data into trusted insight that supports strategic decisions, revenue growth, and long-term financial sustainability. The role reports to the Commercial Analysis and Forecasting Manager, who also oversees Yield Management.

Working closely with Commercial, Marketing, Revenue Protection, Operations, and Timetable Planning, the Revenue Manager sets the analytical direction for the business. The role provides insight into pricing, demand forecasting, marketing performance, revenue protection, and wider commercial optimisation, while ensuring accurate revenue budgets and forecasts and identifying opportunities to improve revenue, capacity utilisation, and customer outcomes.

The Revenue Manager owns the integrity and governance of core datasets and reporting frameworks, championing Power BI, automated reporting, and advanced modelling to deliver timely, high-quality insight. Through effective stakeholder engagement and communication, the role embeds revenue intelligence across the organisation, supporting confident decision-making and effective commercial planning.

Context
Chiltern Railways is a UK train operator running services from London Marylebone to destinations across Buckinghamshire, Oxfordshire, Warwickshire and the West Midlands. Our vision is to make journeys easier, greener, better, and we have a three-phase plan to modernise our fleet with a focus on sustainability, reliability and improving the passenger experience. 

This role will be part of the Commercial Department reporting into the Commercial and Customer Strategy Director.

The role is expected to be office based (3 days per week minimum) with some travel across the network within normal working hours.

Key Accountabilities
Leadership, Strategy & Governance

• Lead Chiltern Railways’ revenue insight and reporting, ensuring analysis is accurate, timely, and aligned with commercial strategy.
• Set analytical direction for the Revenue Analysis team, prioritising workload, developing capability, using digital tools effectively, automating reporting where possible, and championing spreadsheet modelling best practice.
• Develop and implement strategies to maximise yield and earnings across passenger income streams, using insight to shape pricing, product design, and commercial decisions.

Budgeting, Forecasting & Performance Management

• Oversee weekly, periodic, and annual revenue forecasts, providing clear insight into performance drivers, risks, and opportunities.
• Support Chiltern’s business plan, ensuring assumptions are evidence-based and aligned with operational and commercial plans.
• Provide senior stakeholders with clear, actionable commentary on revenue trends, demand patterns, and market dynamics to support strategic and operational decisions.

Revenue Reporting & Insight

• Manage all passenger revenue reporting, ensuring timely weekly and periodic insight with appropriate trend analysis, narrative, and recommendations.
• Oversee analysis of timetable and pricing changes, ensuring modelling and forecasting inform commercial strategy, operational readiness, and customer impact assessments.
• Monitor competitor pricing, service changes, and market movements, translating insight into clear dashboards, risk assessments, and mitigation strategies.

Operational & Capacity Insight

• Lead the analysis of passenger counting data to inform advance ticketing quotas, demand forecasting, and capacity optimisation.
• Oversee analysis from automatic ticket barriers and operational systems, ensuring insight supports train length decisions, crowding management, and operational planning.
• Ensure special event analysis (e.g. Wembley fixtures, engineering works, and major disruptions) supports pricing, planning, and operational readiness.

Industry, Regulatory & Commercial Support

• Twice yearly, oversee the extraction and interpretation of ORCATS data, advising the Head of Commercial on significant changes and their commercial implications.
• Provide senior-level analytical support to Directors for claims disputes, business cases, and commercial negotiations.
• Ensure revenue intelligence is readily available across internal departments to support cross-functional planning, strategic initiatives, and commercial decision-making.

Ad Hoc & Strategic Projects

• Lead ad hoc analytical projects, including evaluations of new retail facilities, operational changes, and commercial initiatives, ensuring outputs are robust, automated where appropriate, and aligned with business priorities.

Personal Specification
Able to work flexibly and at pace, responding to both planned and unplanned priorities.

Strong organisation and time‑management skills, with the ability to manage workload independently and ensure work can be easily picked up by colleagues.

Excellent accuracy and attention to detail, ensuring high‑quality outputs.

 
Experience

• Experience in a data-driven analytical role, ideally covering commercial, operational, or customer insight.
• Experience working with large datasets, data modelling, or automated reporting tools.
• Experience in rail, transport, or another regulated, customer-facing industry is desirable but not essential.
• Experience working with commercial, marketing, operational, or finance teams to provide insight that supports decision-making.
• Degree-level education in a numeric, analytical, or statistical discipline (e.g. Mathematics, Economics, Data Science, Engineering, Geography with quantitative methods, or similar).
• Equivalent experience demonstrating strong analytical capability will also be considered.

Essential

• Strong Microsoft Excel skills, including advanced functions, data manipulation, and modelling.
• Knowledge of railway retail and operational information systems, such as LENNON, MOIRA, RARS, and gateline data systems.
• Working knowledge of Power BI or another business intelligence/visualisation tool, such as Tableau or Qlik.
• Understanding of data analysis techniques, including trend analysis, forecasting, segmentation, and performance measurement.
• Awareness of data quality, data integrity, and the importance of robust reporting.

Desirable

• Familiarity with digital analytics tools and online sales performance metrics.
• Experience with SQL, Python, R, or other data science tools is beneficial, particularly for future capability development.