ML Engineer – Personalisation & Real-Time Recommendations in England

ML Engineer – Personalisation & Real-Time Recommendations in England

England Full-Time 50000 - 70000 Β£ / year (est.) No working from home possible
ASOS

At a Glance

  • Tasks: Design and build systems for personalised product discovery and real-time recommendations.
  • Company: Join ASOS, a leading fashion retailer with a focus on innovation.
  • Benefits: Enjoy employee discounts, 25 days of paid leave, and a vibrant work culture.
  • Other info: Collaborate with data scientists in a dynamic and creative environment.
  • Why this job: Make a real impact on customer experiences through cutting-edge machine learning.
  • Qualifications: Experience in machine learning solutions and familiarity with modern frameworks.

The predicted salary is between 50000 - 70000 Β£ per year.

ASOS is seeking a Machine Learning Engineer to join the Search & Recommendations team, where you will design and build systems that personalize product discovery. This role involves collaborating with data scientists and deploying models that directly influence customer experiences.

Candidates should have experience in machine learning solutions and familiarity with modern frameworks.

The position offers benefits like employee discounts and 25 days of paid annual leave.

ML Engineer – Personalisation & Real-Time Recommendations in England employer: ASOS

ASOS is an excellent employer for those passionate about technology and innovation, offering a dynamic work culture that fosters collaboration and creativity. With opportunities for professional growth and development, employees benefit from a supportive environment where their contributions directly enhance customer experiences. Located in a vibrant area, ASOS also provides attractive perks such as employee discounts and generous annual leave, making it a rewarding place to build a career.

ASOS

Contact Details:

ASOS Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land ML Engineer – Personalisation & Real-Time Recommendations in England

✨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 ASOS!

✨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 Engineer – Personalisation & Real-Time Recommendations at ASOS.

✨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 ASOS.

✨Apply Directly through Our Website

When you find a suitable opening like ML Engineer – Personalisation & Real-Time Recommendations at ASOS, 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 Engineer – Personalisation & Real-Time Recommendations in England

Machine Learning
Personalisation
Real-Time Recommendations
Collaboration
Model Deployment
Data Science
Modern Frameworks

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 ASOS, 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 ASOS. 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 ASOS

✨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 ASOS!

✨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.