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- Tasks: Design and enhance machine learning solutions for personalised recommendations.
- Company: Leading online marketplace in Greater London with a focus on innovation.
- Benefits: Flexible working, comprehensive health benefits, and a supportive culture.
- Why this job: Join a team that values creativity and makes a real impact in AI.
- Qualifications: Experience in deep learning and Python, with a passion for innovation.
- Other info: Great opportunities for learning and professional development.
The predicted salary is between 36000 - 60000 £ per year.
A leading online marketplace in Greater London is seeking a Machine Learning Scientist to enhance personalization through advanced recommendation systems.
Responsibilities include:
- Designing machine learning solutions
- Collaborating cross-functionally
- Conducting experiments to improve models
Ideal candidates will have:
- Experience in deep learning and Python
- A passion for innovation
This position offers flexible working, comprehensive health benefits, and a supportive culture focused on learning and development.
ML Scientist, Recommendations — Scale Personalised AI employer: Depop
Contact Detail:
Depop Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Scientist, Recommendations — Scale Personalised AI
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow ML enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those involving recommendation systems. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your deep learning knowledge and Python skills. Practice explaining your past projects and how they relate to the role. We want to see your passion for innovation shine through!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace ML Scientist, Recommendations — Scale Personalised AI
Some tips for your application 🫡
Show Your Passion for Innovation: When writing your application, let us see your enthusiasm for machine learning and innovation. Share any personal projects or experiences that highlight your creativity and problem-solving skills in this field.
Tailor Your Experience: Make sure to customise your CV and cover letter to reflect the specific skills mentioned in the job description. Highlight your experience with deep learning and Python, as these are key to the role we're looking to fill.
Collaborate in Your Application: Since collaboration is a big part of our culture, mention any cross-functional projects you've worked on. This shows us you can work well with others and contribute to a team environment.
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 don’t miss out on any important updates during the process.
How to prepare for a job interview at Depop
✨Know Your ML Fundamentals
Brush up on your machine learning concepts, especially around recommendation systems. Be ready to discuss algorithms you've used and how they can be applied to enhance personalisation. This shows your depth of knowledge and passion for the field.
✨Showcase Your Python Skills
Prepare to demonstrate your proficiency in Python during the interview. You might be asked to solve a coding problem or explain your previous projects. Practising common ML libraries like TensorFlow or PyTorch can give you an edge.
✨Collaborative Mindset
Since the role involves cross-functional collaboration, think of examples where you've worked with different teams. Highlight your communication skills and how you’ve successfully shared insights or tackled challenges together.
✨Embrace Innovation
Be ready to discuss your passion for innovation in machine learning. Share any unique projects or experiments you've conducted that pushed the boundaries of traditional methods. This will resonate well with their focus on learning and development.
