SENIOR REVENUE ANALYST

Get-e's transport division runs the rides behind airlines, travel management companies and assistance companies: crew transfers at 3 a.m., a patient going from hospital to the airport, a traveller landing in a city they've never seen. We book, manage and monitor ground transportation in 110+ countries, through a network of local providers and a 24/7 operations team.

Our pricing engine handles 5,000 to 10,000 price requests per second. Every ride has two numbers: what the client pays and what the provider costs us. Across thousands of routes, cities, vehicle types and contracts, the gap between those two numbers decides whether we grow profitably.

Your will work in the Travel Partnerships team, and you own both sides: how many requests turn into booked rides, and how much we make on each one. Those are your KPIs, and you're measured on them.

And it's not only about price. A request that can't be booked because we have no supplier, too few suppliers or the wrong vehicles in that city or airport is a gap in our network. You find those gaps in the data and work with Supply to close them, so a client is never presented with no supply.

This is a hands-on analytical role. You don't wait for a data engineer to prepare a dataset or build a report. You go into the raw data yourself, clean it, model it and come back with the answer. If that's how you already work, read on. If you're used to directing analysis rather than doing it, this role isn't for you.

You'll work with Commercial, Operations, Supply and Tech. Your analysis feeds daily pricing decisions, supplier negotiations, new products and the pricing logic in our platform.

• Your work shows up directly in the P&L. In our business a few percent of margin is a big deal, and your impact will be visible.
• A small, international team (100+ people, 30+ nationalities, offices in Hoofddorp and Manila) where decisions are made quickly and analysts have a voice.
• Hard problems to work on: global supply, B2B contracts, 24/7 operations and a platform we're actively rebuilding.
• Hybrid working: 2 days from home, plus the option to work 2 weeks from abroad.
• 15 vacation days and 15 sick leave days per year.
• Partial reimbursement of travel expenses and office parking.
• Two rides a year with our own service, anywhere in the world.
• Free snacks and drinks in the office pantry.

• Own KPIs, such as, request-to-booking conversion and margin per ride. Set the targets, track them, and explain every movement.
• Own the path from price request to booked ride: dig into the request data yourself to find where and why requests don't convert, and fix it.
• Find the gaps in our network: where requests fail or don't convert because there's no supplier, too few suppliers or the wrong vehicle types. Rank them by volume and value, and work with Supply to close them so clients always get a result.
• Set pricing strategy across partners, regions, routes, vehicle types and suppliers, down to country, city, airport and zone level.
• Compare sell price with supplier cost to find margin that's too thin, too high or at risk. Benchmark against the market to see where we're priced out.
• Build and maintain your own analyses, models and dashboards end to end, from raw data to recommendation.
• Define how the platform picks the right supplier and vehicle for each request, balancing price, margin and service.
• Work with engineers to turn pricing strategy into rules the engine can run, returning correct prices within two seconds.
• Design and run pricing tests, measure the results with statistical rigour, and adjust when the numbers don't hold.
• Design cancellation policies and fees that are fair to clients and protect our margin.
• Find pricing errors, outdated rates and margin leakage, and fix them at the source.
• Give Supply the cost data and targets they need for negotiations.

• 5+ years in pricing strategy, revenue management, conversion optimisation or a similar analytical role
• A proven track record of doing your own data analysis end to end: you query, clean, join and model large, messy datasets yourself, without relying on data engineers or BI teams to prepare them for you
• Advanced SQL (window functions, CTEs, complex joins, performance on large tables). This is a daily tool for you, not something you pick up occasionally
• Python for analysis and modelling where SQL stops
• A solid grounding in statistics and experiment design: you know when a result is real and when it's noise
• Experience owning KPIs and being accountable for moving them
• Experience with dynamic or automated pricing in a marketplace, platform or other high-volume business
• Experience working with engineers to turn pricing strategy into rules or algorithms
• The ability to explain numbers clearly to people who aren't analysts, in writing and in meetings
• Fluent English, written and spoken