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- Tasks: Manage the complete model-building process and improve algorithms for a privacy-focused platform.
- Company: Join a cutting-edge transportation platform in Greater London.
- Benefits: Enjoy flexible working hours, stock options, and medical insurance.
- Why this job: Make an impact in the transportation sector while developing your skills.
- Qualifications: STEM degree, 2 years of experience, and strong Python skills required.
- Other info: Great perks and professional development opportunities await you!
The predicted salary is between 48000 - 72000 £ per year.
A privacy-focused transportation platform in Greater London is seeking mid-level and senior Data Scientists / ML Engineers. You will manage the complete model-building process, from ideation to production.
Responsibilities include improving algorithms and developing proofs of concept.
Ideal candidates possess a STEM degree, 2 years of experience, and strong Python skills.
The position offers flexible working hours, stock options, and various perks including medical insurance and professional development opportunities.
Senior Data Scientist & ML Engineer – Production Models in London employer: Wheely
Contact Detail:
Wheely Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist & ML Engineer – Production Models in London
✨Tip Number 1
Network like a pro! Reach out to current employees at the company through LinkedIn or industry events. A friendly chat can give us insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best data models and algorithms. We want to see your work in action, so make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for the technical interview! Brush up on your Python skills and be ready to discuss your past projects. We recommend practicing common data science problems to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the quickest way to get noticed. Plus, we love seeing candidates who take the initiative to apply directly. Don’t miss out on this opportunity!
We think you need these skills to ace Senior Data Scientist & ML Engineer – Production Models in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python skills and any relevant experience in data science or machine learning. We want to see how you’ve tackled real-world problems and improved algorithms in your past roles.
Tailor Your Application: Don’t just send a generic CV and cover letter. Take the time to tailor your application to our job description. Mention specific projects or experiences that align with managing the model-building process from ideation to production.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and enthusiasm for the role.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the position. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Wheely
✨Know Your Algorithms
Brush up on your understanding of algorithms and model-building processes. Be ready to discuss specific algorithms you've worked with, how you improved them, and the impact they had on your projects.
✨Showcase Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges that relate to data science and machine learning.
✨Prepare for Scenario Questions
Expect scenario-based questions where you'll need to explain how you would approach a specific problem. Think about past experiences where you developed proofs of concept or improved existing models, and be ready to share those stories.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects, the tools they use, or how they measure success in their models. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
