At a Glance
- Tasks: Build and implement machine learning models to solve real-world problems.
- Company: Wheely, a unique ride-hailing company focused on privacy and five-star service.
- Benefits: Equity options, relocation support, private medical insurance, and professional development stipends.
- Other info: Collaborative environment with opportunities for growth and innovation.
- Why this job: Join a dynamic team tackling exciting challenges in data science and machine learning.
- Qualifications: STEM degree from a top university and 1-2 years of relevant experience.
The predicted salary is between 40000 - 50000 € per year.
We are looking for junior-level, mid-level and senior Data Scientists / ML Engineers at Wheely. You will own the entire process of building, from initial ideation and research to implementation of models in production. You will join one of our three marketplace teams (matching/pricing/mapping) - working on difficult problems such as predicting ETAs, dispatching immediate and future requests as well as pricing journeys to maximize demand & supply.
Company
Wheely is not a traditional ride-hailing company. We believe in privacy and building our platform with that principle at its core, while successfully scaling a five-star service to thousands of chauffeurs across multiple cities in EMEA. We hire for data science roles in London (where Wheely HQ is located) and Nicosia (Cyprus) depending on the level.
Responsibilities
- Work with a cross-functional team of engineers, designers and product managers to solve ambiguous problems and implement algorithms in production.
- Building new proofs of concept and improving existing algorithms.
- Researching and then delivering PoC into products.
Requirements
- STEM degree from a top 3 university in your country.
- 1-2 years of experience in Data Science / Machine Learning or similar.
- Excellent programming skills in Python and relevant tools.
- Deep understanding of fundamentals of probability and statistics.
Working conditions
- Equity in the form of stock options.
- Relocation allowance to cover flights/initial accommodation and 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.
Data Scientist - Matching/ Pricing/ Mapping/ Billing employer: Open Data Science
Wheely is an exceptional employer that prioritises privacy and a five-star service, creating a unique work environment for Data Scientists in London and Nicosia. With a strong focus on professional development, employees benefit from equity options, relocation assistance, and a collaborative culture that encourages innovation and problem-solving. Join us to tackle challenging problems while enjoying perks like office lunches and private medical insurance.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Matching/ Pricing/ Mapping/ Billing
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Wheely on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your Python skills and understanding the latest in machine learning. We recommend doing some mock interviews with friends or using online platforms to get comfortable with common questions.
✨Tip Number 3
Showcase your projects! If you've built any models or worked on relevant data science projects, make sure to have them ready to discuss. We love seeing practical applications of your skills during interviews.
✨Tip Number 4
Don’t forget to apply 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 joining the Wheely team.
We think you need these skills to ace Data Scientist - Matching/ Pricing/ Mapping/ Billing
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role at Wheely. Highlight your relevant experience in machine learning, programming skills in Python, and any projects that showcase your problem-solving abilities. We want to see how you can contribute to our marketplace teams!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how your skills align with Wheely's mission. Don’t forget to mention specific projects or experiences that relate to matching, pricing, or mapping.
Showcase Your Projects:If you've worked on any interesting data science projects, make sure to include them in your application. Whether it's a proof of concept or an algorithm you've implemented, we love seeing real-world applications of your skills. It helps us understand your thought process and creativity!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application directly and ensures you don’t miss out on any important updates from our team. We can’t wait to hear from you!
How to prepare for a job interview at Open Data Science
✨Know Your Algorithms
Brush up on your understanding of algorithms and models relevant to data science, especially those used in matching, pricing, and mapping. Be ready to discuss how you would implement these in production and provide examples from your past experience.
✨Showcase Your Problem-Solving Skills
Prepare to tackle ambiguous problems during the interview. Think of specific challenges you've faced in previous roles and how you approached them. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Familiarise Yourself with Wheely's Values
Understand Wheely's commitment to privacy and high-quality service. Be prepared to discuss how your values align with theirs and how you can contribute to their mission of scaling a five-star service.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the technologies they use, and the challenges they face. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
