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- Tasks: Join us to build innovative models for traffic forecasting and enhance our mapping technology.
- Company: Wheely is a leading company in geo services, focused on delivering seamless product experiences.
- Benefits: Enjoy flexible hours, stock options, medical insurance, and a lunch allowance.
- Why this job: This role offers a chance to blend data science with real-world impact in a collaborative environment.
- Qualifications: A background in geo tech, machine learning, or data analytics is preferred; advanced degrees are a plus.
- Other info: Located in West London, this role supports both in-office and remote work flexibility.
The predicted salary is between 43200 - 72000 £ per year.
At Wheely, we are building the future of high-end transportation. We\’re pioneering a new standard of excellence and crafting unparalleled brand, product and service experiences for discerning individuals who prioritize time and perfection above all else. Join us as we scale Wheely from London, Dubai and Paris to dozens of markets around the world in the coming years. With over 3000 chauffeur partners and hundreds of thousands of customers, we are fortunate to be the leading brand in all the markets we operate in. We are looking for a Data Scientist to join the Wheely for Mapping team. 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 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. #J-18808-Ljbffr
Data Scientist (Maps) employer: Wheely
Contact Detail:
Wheely Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Maps)
✨Tip Number 1
Familiarize yourself with geo tech applications and graph theory. Understanding these concepts will not only help you in interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Showcase any practical experience you have with predictive machine learning or simulation. If you've worked on relevant projects, be ready to discuss them in detail during your conversations with us.
✨Tip Number 3
Prepare to discuss how you've deployed solutions to production in the past. Highlighting your ability to measure impact will set you apart from other candidates.
✨Tip Number 4
Engage with our current products and think about potential improvements or innovations. Bringing fresh ideas to the table can show us that you're proactive and passionate about enhancing user experience.
We think you need these skills to ace Data Scientist (Maps)
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Data Scientist (Maps) position. Highlight the key responsibilities and requirements, such as experience in predictive machine learning and understanding of geo tech applications.
Tailor Your CV: Customize your CV to reflect your relevant experience and skills that align with the job. Emphasize your background in data science, any projects related to geo services, and your ability to work in cross-functional teams.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and geo technology. Mention specific examples of your work that relate to the responsibilities listed in the job description, such as building machine learning models or improving metrics dashboards.
Highlight Your Technical Skills: In your application, clearly outline your technical skills relevant to the role, such as programming languages, tools, and frameworks you are proficient in. Include any experience with deploying solutions to production and measuring their impact.
How to prepare for a job interview at Wheely
✨Showcase Your Data Science Skills
Be prepared to discuss your experience with heuristic and machine learning models. Highlight specific projects where you've implemented algorithms in production, especially those related to ETA correction or traffic forecasting.
✨Demonstrate Your Understanding of Geo Tech
Since the role involves geo services, make sure to articulate your knowledge of graph theory and geo tech applications. If you have practical experience, share examples that illustrate your expertise.
✨Collaborate Effectively
The job requires working with cross-functional teams. Prepare to discuss how you've successfully collaborated with engineers, designers, and product managers in the past to solve complex problems.
✨Prepare for Technical Questions
Expect technical questions related to data analytics and predictive machine learning. Brush up on relevant concepts and be ready to explain your thought process when tackling ambiguous problems.
