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- Tasks: Build predictive models and optimise decision systems for real-world fleet operations.
- Company: Odysse, a pioneering mobility tech company in London.
- Benefits: Competitive salary, hybrid work model, and potential for full-time conversion.
- Why this job: Make a tangible impact on urban mobility and future autonomous vehicle networks.
- Qualifications: 3-5 years in Data Science, strong Python and SQL skills required.
- Other info: Collaborate with senior leaders and global partners on innovative projects.
The predicted salary is between 39600 - 66000 £ per year.
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.
Data Scientist in London employer: Odysse Ltd.
Contact Detail:
Odysse Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in London
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at Odysse. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your projects, especially those involving Python, SQL, or machine learning. Real-world examples of your work can make you stand out.
✨Tailor Your Approach
Before any interview, do your homework on Odysse and their projects. Show them you understand their mission in mobility tech and how your skills can contribute to their goals. Personalisation goes a long way!
✨Apply Through Our Website
Don’t forget to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the team.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, SQL, and any relevant machine learning projects. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for mobility technology and how your background in data science can contribute to our mission at Odysse. Keep it engaging and personal.
Showcase Relevant Projects: If you've worked on projects involving geospatial or time-series data, make sure to mention them! We love seeing practical examples of your work that demonstrate your ability to tackle real-world problems.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Odysse Ltd.
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around machine learning and predictive modelling. Be ready to discuss your experience with Python, SQL, and any advanced techniques you've used, like neural networks or optimisation methods.
✨Understand the Company’s Mission
Dive into Odysse's work in mobility technology and how their AI-driven systems operate. Knowing how your role as a Data Scientist fits into their vision will show that you're genuinely interested and can contribute meaningfully to their projects.
✨Prepare Real-World Examples
Think of specific instances where you've tackled complex data problems or optimised processes. Be ready to explain your thought process, the challenges you faced, and the impact your solutions had. This will demonstrate your practical experience and problem-solving skills.
✨Ask Insightful Questions
Prepare some thoughtful questions about the team dynamics, ongoing projects, or future challenges in fleet orchestration. This not only shows your enthusiasm but also helps you gauge if the company culture and goals align with your own.