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Senior Data Analyst

Job in Greenwich, Fairfield County, Connecticut, 06831, USA
Listing for: Future of London
Full Time position
Listed on 2026-02-15
Job specializations:
  • Finance & Banking
    Financial Analyst
  • Business
    Financial Analyst
Salary/Wage Range or Industry Benchmark: 81822 USD Yearly USD 81822.00 YEAR
Job Description & How to Apply Below

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Job Details
  • Job title – Data Analyst (Band
    3)
  • Band – Band 3
  • Salary – from £60,000 (based on experience)
  • Location – Greenwich (Peir Walk)/ Hybrid
  • Contract Type – Permanent (TfL)
Job Role

The Senior Revenue Analysts provide high‑level support for their line managers, analysing the patterns and nature of passenger travel and revenues and/or evaluating proposals for ticketing system developments, all of which underpin decisions in many areas such as allocation of revenue from multi‑modal tickets, income forecasting, evaluation of fare options and assessment of future ticketing system changes. The job holders draw on a wide range of information ranging from internal data on ticket sales, revenues, Oyster usage data, etc.,

external data on inflation, economic activity, etc., and undertake a wide variety of analytical tasks, for example building econometric models to explain trends, estimating the usage of Travel cards on each mode to support revenue allocation, forecasting the effects of fare changes. The job holders will also evaluate proposals for changes to the ticketing systems/models, in particular the development of a new Travelcard allocation model and expansion of Contactless Payment Cards, in relation to the above activities.

Key

Accountabilities
  • Analyse and interpret fare revenue and ridership data and the factors affecting them, together with development of the appropriate statistical models, to provide an explanation of trends for senior management across all TfL modes and National Rail, together with revenue and ridership forecasts.
  • Evaluate the impact on revenue, ridership and customers of fare revision options and ticketing initiatives across all TfL public transport modes and National Rail in London, developing established computer models and creating ad‑hoc new ones as required to understand the financial and other impacts of fare and ticketing changes.
  • Apply the various analytical processes set out in the ticketing agreements (Travelcard, Through Ticketing, PAYG, etc.) to derive factors, percentages, payment amounts, etc., which determine the shares of revenue from joint tickets to be allocated to each of the various TfL operators (LUL, Buses, DLR, Tramlink, Overground) and to the National Rail train operating companies (total revenue circa £4 billion per annum).
  • Continuously monitor the operation of, and results from, the system for apportioning PAYG revenue operated by the Technology Strategy & Revenue team, to ensure that all revenue is apportioned in accordance with the PAYG and CPAY agreements, that system upgrades are compliant with requirements, and that emerging issues affecting the National Rail companies are addressed and disputes avoided.
  • Provide analytical support to the Technology Strategy & Revenue team regarding the expansion of CPCs as a new ticketing medium, to ensure that the new system supports the necessary back‑office processes.
  • Negotiate, develop and agree with London Councils, appropriate econometric models to assess the revenue losses and other costs of the Freedom Pass scheme to TfL to underpin TfL’s claim for compensation from the London Boroughs.
  • Develop, populate and maintain a variety of major databases ranging from internal ticket sales, revenue and passenger usage information through to externally‑sourced economic series, in order to support the multiplicity of analytical and modelling tasks as described in the accountabilities above.
  • Provide a wide range of ad‑hoc analyses, as required, of Oyster, CPC and other ticketing data, and develop the necessary expertise and familiarity with the relevant databases in order that non‑routine and novel data analyses can be readily produced.
Knowledge, Skills & Experience Knowledge
  • Ability to apply advanced computer‑based analytical knowledge/techniques, e.g. SQL, Power BI, Databricks, Excel, and to build appropriate computer models.
  • Deep understanding of the Oyster ticketing system and the way in which ticket usage and sales data is held and can be interrogated.
  • Good understanding of the various travel agreements and the provisions governing revenue sharing.
  • Thorough knowledge of…
Position Requirements
10+ Years work experience
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