ML Scientist – Ranking & Personalization (Remote/Hybrid) in London

ML Scientist – Ranking & Personalization (Remote/Hybrid) in London

London Full-Time 70000 - 90000 Β£ / year (est.) Home office (partial)
Depop

At a Glance

  • Tasks: Create advanced ranking models to enhance user experience on our app.
  • Company: Join DEPOP, a leading platform in the fashion resale market.
  • Benefits: Flexible working options, health benefits, and continuous learning opportunities.
  • Other info: Supportive environment that fosters innovation and career growth.
  • Why this job: Make a real impact on millions of users with your machine learning expertise.
  • Qualifications: Strong skills in Python and experience with machine learning frameworks.

The predicted salary is between 70000 - 90000 Β£ per year.

DEPOP is seeking a Machine Learning Scientist to build advanced ranking models for our app. You will be pivotal in enhancing the app's user experience for millions.

Responsibilities include:

  • Designing machine learning solutions
  • Collaborating with teams
  • Researching new ML techniques

The ideal candidate has strong expertise in Python and ML frameworks.

Enjoy a range of perks including flexible working options, health benefits, and a supportive environment for continuous learning.

ML Scientist – Ranking & Personalization (Remote/Hybrid) in London employer: Depop

DEPOP is an exceptional employer that champions innovation and collaboration, making it an ideal place for a Machine Learning Scientist to thrive. With flexible working options, comprehensive health benefits, and a strong commitment to employee growth, DEPOP fosters a supportive environment where you can enhance your skills while contributing to the user experience of millions. Join us in a culture that values creativity and continuous learning, all from the comfort of your own home or in a hybrid setting.

Depop

Contact Details:

Depop Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land ML Scientist – Ranking & Personalization (Remote/Hybrid) in London

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Depop!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like ML Scientist – Ranking & Personalization (Remote/Hybrid) at Depop.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Depop.

✨Apply Directly through Our Website

When you find a suitable opening like ML Scientist – Ranking & Personalization (Remote/Hybrid) at Depop, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace ML Scientist – Ranking & Personalization (Remote/Hybrid) in London

Machine Learning
Ranking Models
Python
ML Frameworks
Collaboration
Research Skills
User Experience Enhancement

Some tips for your application 🫑

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Depop, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Depop. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Depop

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Depop!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.