At a Glance
- Tasks: Develop personalisation features and enhance ML functions in a dynamic retail environment.
- Company: Exciting Series A Scale-Up in the Retail space with a focus on innovation.
- Benefits: Competitive salary of £90k-£150k, equity, and hybrid working options.
- Other info: Opportunity for career growth in a vibrant Central London setting.
- Why this job: Join a fast-growing team and make a real impact in personalisation and recommendations.
- Qualifications: Strong STEM background and experience in scaling organisations.
The predicted salary is between 90000 - 150000 € per year.
Oliver Bernard has partnered with a Series A Scale-Up in the Retail space looking for a Machine Learning expert to enhance their ML function. In this role, you will develop personalisation features, including Recommendation and Ranking systems, using your solid background in Data Science.
Ideal candidates will have experience in scaling organizations and a strong STEM academic background.
The position offers a base salary of £90k-£150k, plus equity, with hybrid working in Central London.
ML Engineer - Personalization & Recommendations (Equity) employer: Oliver Bernard
Join a dynamic and innovative Scale-Up in the Retail sector, where your expertise as an ML Engineer will directly impact the development of cutting-edge personalisation features. With a competitive salary package, equity options, and a hybrid working model in the vibrant heart of Central London, you'll thrive in a collaborative work culture that prioritises employee growth and encourages creative problem-solving. This is an exceptional opportunity to be part of a forward-thinking team that values your contributions and supports your professional journey.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer - Personalization & Recommendations (Equity)
✨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 personalisation features and recommendation systems. Use platforms like GitHub to share your projects and demonstrate your expertise in ML.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past experiences in scaling organisations. Practice common ML interview questions to boost your confidence.
✨Tip Number 4
Apply through our website! We make it easy for you to find roles that match your skills. Plus, we’re always on the lookout for talented individuals like you to join our team and help us grow.
We think you need these skills to ace ML Engineer - Personalization & Recommendations (Equity)
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience in Machine Learning and Data Science. We want to see how you've developed personalisation features or recommendation systems in the past, so don’t hold back!
Tailor Your Application:Take a moment to customise your CV and cover letter for this role. Mention specific projects or achievements that align with the job description, especially those related to scaling organisations.
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it's necessary. Make it easy for us to see why you’re the perfect fit!
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at Oliver Bernard
✨Know Your ML Fundamentals
Brush up on your machine learning concepts, especially around personalisation and recommendation systems. Be ready to discuss algorithms you've used and how they can be applied to real-world retail scenarios.
✨Showcase Your Projects
Prepare to talk about specific projects where you've implemented ML solutions. Highlight your role, the challenges you faced, and the impact your work had on the organisation. This will demonstrate your hands-on experience.
✨Understand the Company’s Needs
Research the company and its current ML function. Think about how your skills can enhance their personalisation features. Tailor your answers to show that you understand their goals and how you can contribute.
✨Ask Insightful Questions
Prepare thoughtful questions about the team, the technology stack, and future projects. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
