Wheely is redefining premium transportation across major cities in Europe, the US, and the Middle East. 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.
We’re a profitable, fast-growing scale-up with $43M raised and over $100M in annual revenue. 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.
- 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
- 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
- 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
Wheely expects the very best from our people, both on the road and in the office. In return, employees enjoy flexible working hours, stock options and an exceptional range of perks and benefits.
- Competitive salary
- Equity in the form of stock options
- We provide a relocation allowance to cover flights/ initial accommodation, and we also provide visa sponsorship and assistance.
- Office lunches, as Wheely has an in-person culture
- Private medical insurance
- Newest Mac equipment
- Professional development. An annual stipend to use for continuing education courses, programs, conference or certifications.
All of your personal information will be collected stored and processed in accordance with Wheely’s Candidate Privacy Notice
Top Skills
Wheely London, England Office
The Old Monastery Barn, London, United Kingdom, TW8 8JF
