Data Scientist (Maps)
London, England, United Kingdom
Wheely
Exquisite chauffeured experiences, available in advance and on demand, for you or for others. Reserve a perfect commute or airport transfer in just seconds.At Wheely, we're a luxury brand on the outside, but a technology company on the inside, building the world's first Luxury-as-a-Service. We believe that time is the ultimate luxury and that modern engineering and design, combined with the industry’s highest standards of service, can unlock an unparalleled experience for our customers. From on-demand chauffeuring, concierge service, to our best-in-class app, we exist to help our clients reclaim their time by connecting them to the places and people that matter.
More than 40% of our team works in product & engineering, and both Wheely founders are technical. We are also unapologetically design centric. It’s not about A/B testing one hundred shades of blue, but crafting the perfect shade. We also take a privacy-first approach and believe that where people travel, and who they travel with, is at their discretion.
We have refused government requests to hand over journey data, and are currently developing bespoke technology to put our clients’ movements beyond even our own reach.
Backed by leading global investors, Wheely is poised for the next phase of our journey. Over the next 5-10 years, we plan to offer a full portfolio of luxury services and expand into more international cities, building on our success in London, Paris, and Dubai.
It’s very hard to find a company product without geo services involvement. From the mechanic heart of the system to the polished passenger application you will find to name a few: routing, map display, differential privacy for location data and map matching. While a lot of mapping tech comes from commercial third-party solutions, we implement a fair share of in-house ideas. And the more the business grows, the more the innovations are needed. This is where you have a great opportunity to mix your strong data science skills with your passion to deliver the seamless product experience to every part of our system.
Responsibilities
- Help build heuristic and machine learning models for ETA correction, next 30-second car position, traffic speed forecasting and more.
- Work with a cross-functional team of engineers, designers and product managers to solve ambiguous problems and implement algorithms in production.
- Research current system deficiencies and behaviour.
- Create / improve metrics dashboards to understand maps situation at any given time.
Requirements
- Understanding of geo tech application or graph theory, practical experience is a huge plus.
- Experience in predictive machine learning or simulation, data analytics.
- PhD or Master's degree in computer science, statistics, or related quantitative fields is a plus.
- Proven experience of deploying solutions to production and measuring the impact.
What we offer
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.
- Office-based role located in West London
- Competitive salary & equity package
- Medical insurance, including dental
- Life and critical illness insurance
- Monthly credit for Wheely journeys
- Lunch allowance
- Professional development subsidies
- Cycle to work scheme
- Top-notch equipment
- Relocation allowance (dependent on role level)
- Wheely has an in-person culture but allows flexible working hours and work from home when needed.
Wheely is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
All of your personal information will be collected stored and processed in accordance with Wheely’s Candidate Privacy Notice
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: A/B testing Computer Science Data Analytics Engineering Machine Learning ML models PhD Privacy Research Statistics Testing
Perks/benefits: Career development Competitive pay Equity / stock options Flex hours Gear Relocation support
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