Data Scientist – Mobility & Operations Intelligence (Contract)
London (Croydon) (Hybrid – typically 3 days per week in office)
6–7 Month Contract (Strong likelihood of full-time conversion)
Approx. £55,000 annualised equivalent (depending on experience)
About Odysse
Odysse is a London-based mobility technology company building intelligent fleet orchestration systems for ride-hailing and future autonomous vehicle (AV) networks.
Our AI-driven decision systems influence real-world behaviour: Where vehicles move, how cities are served, and how efficiently transportation operates. We are designing the optimisation and data infrastructure that supports both today's human-driven fleets and tomorrow's autonomous mobility networks.
This is a hands-on applied machine learning role focused on building and improving decision systems that directly influence live fleet operations and contribute to long-term autonomous fleet orchestration capabilities.
You will work on logistics optimisation, real-time decision systems, simulation and operational experimentation, applying ML in complex, real-world environments.
What You'll Work On
Build predictive models using geospatial and time-series data (demand, driver behaviour, trip outcomes) and evaluate them using operational business metrics
Partner with operations and senior team members to translate operational challenges into measurable ML problems and propose appropriate modelling approaches
Engineer features, analyse large datasets using Python and SQL, and identify useful external data sources
Design and support experiments contributing to fleet positioning and planning decisions
Contribute to modelling and simulation work that supports long-term autonomous fleet orchestration and mixed-fleet (human driven + Autonomous Vehicle) operational planning
Collaborate with operations and engineering to deploy and improve data-driven workflows
Support related technical or analytical initiatives across the company (e.g. data integrations, tooling improvements, analytical inputs into product and operations)
We're Looking For Someone Who
Ideally has 3-5 years' experience in Data Science / Applied ML / Analytics (years of experience provided as a guide)
Can independently train, evaluate and iterate on models given a clearly defined problem
Is comfortable with Python (pandas/numpy/sklearn or similar), strong SQL, and relational databases
Can work with imperfect real-world data and optimise for practical impact rather than just model accuracy
Has exposure to advanced modelling approaches (e.g. neural networks, optimisation, or reinforcement learning)
Nice to Have
Experience with time-series or geospatial datasets, experimentation or optimisation problems
Experience in logistics, marketplaces, mobility systems, ride-hailing or autonomous vehicle ecosystems
Why This Role Is Different
Your models affect physical movement in a city, not just clicks on a screen
Exposure to real operational decision systems used in live fleet environments
Opportunity to help build the data and optimisation foundations for future autonomous vehicle networks
Work across modelling, experimentation and deployment in a product environment shaping next-generation mobility
Work closely with senior leadership team, with exposure to global corporate partners, interacting with venture capital and strategic funders, on ambitious projects shaping the future of mobility