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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, • 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, • Experience with time-series or geospatial datasets, experimentation or optimisation problems, • 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

A leading trading firm in London is seeking a Quant Data Engineer to work on impactful trading projects.This mid-senior level role requires 5+ years of experience with a strong focus on Python and data analysis.You will collaborate with top researchers and traders, optimizing algorithms and enhancin