At a Glance
- Tasks: Own the entire data science process from ideation to production deployment.
- Company: Rapidly expanding tech company blending technology with five-star chauffeuring.
- Benefits: Competitive salary, stock options, private medical insurance, and flexible working hours.
- Other info: Office-based role in West London with excellent career growth opportunities.
- Why this job: Join a dynamic team solving high-impact problems with cutting-edge ML technology.
- Qualifications: Strong STEM background and 2+ years in Data Science or Machine Learning.
The predicted salary is between 90000 - 110000 £ per year.
We blend cutting-edge technology with the craft of five-star chauffeuring to deliver an experience trusted by more than 100,000 active riders and 1,200 corporate accounts. Having recently launched in New York City, we're expanding rapidly across the US and EMEA. If you take pride in your craft and want to help shape the next chapter of our growth, we'd love to hear from you.
About The Role
We're hiring mid-level and senior Data Scientists / ML Engineers. You will own the entire process: from ideation and research through to production deployment. You'll join one of several hiring teams (Mapping, Matching, Pricing, or Supply) tackling challenging & high-impact problems such as ETA prediction, routing, map matching, dynamic pricing, bipartite matching, driving style prediction, and LLM integration.
Responsibilities
- Collaborate with engineers, designers, and product managers to solve ambiguous problems
- Research, prototype, and ship ML models into production
- Continuously improve existing algorithms and identify opportunities for new ones
Requirements
- Strong academic background in a STEM field
- 2+ years of experience in Data Science or Machine Learning for mid-level; 5+ years for senior roles
- Strong foundation in probability & statistics
Nice To Have
- Experience with geospatial data or routing (particularly relevant for the Mapping team)
- Background in operations research or combinatorial optimization (particularly relevant for the Matching and Pricing teams)
- Experience deploying real-time or latency-sensitive ML systems
What We Offer
- Office-based role in West London, four days a week with flexible start and finish times, plus one remote day of your choice
- Salary: 90,000 – 110,000
- Employee stock options plan
- Private medical and dental insurance
- Life and critical illness cover
- Latest-generation MacBook Pro and 4k display
- Monthly credit towards Wheely journeys
- Cycle to Work scheme
- Professional development stipend
- Relocation support, including visa sponsorship and allowance
All of your personal information will be collected stored and processed in accordance with Wheely's Candidate Privacy Notice.
Data Scientist Ml Ai Python in London employer: Wheely
At Wheely, we pride ourselves on being an innovative employer that values the craft of our team members while fostering a collaborative and dynamic work environment. Located in West London, we offer flexible working arrangements, comprehensive benefits including private medical insurance, and a commitment to professional development, ensuring our employees have the tools and support they need to thrive. Join us as we shape the future of luxury transportation and enjoy the unique opportunity to make a significant impact in a rapidly growing company.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist Ml Ai Python in London
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Wheely.
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We think you need these skills to ace Data Scientist Ml Ai Python in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Wheely, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Wheely. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Wheely
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Wheely!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
