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- Tasks: Lead the development of predictive models and recommendation systems for customer engagement.
- Company: Global fashion retailer with a focus on innovation and customer experience.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact in personalising customer experiences in the fashion industry.
- Qualifications: Proficiency in Python and experience with machine learning operations.
- Other info: Join a dynamic team and shape the future of fashion retail.
The predicted salary is between 36000 - 60000 £ per year.
A global fashion retailer is seeking a passionate Data Scientist Manager to lead personalization efforts within its CRM ecosystem. The ideal candidate will develop predictive models and recommendation systems to enhance customer engagement across markets.
Responsibilities include:
- Leading machine learning solutions development
- Optimizing recommendation engines
- Collaborating with marketing and engineering teams
Proficiency in Python and experience with ML Ops are essential for this role.
Data Science Manager: Personalization & Recommendations employer: Ralph Lauren
Contact Detail:
Ralph Lauren Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager: Personalization & Recommendations
✨Tip Number 1
Network like a pro! Reach out to folks in the fashion and data science industries on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and recommendation systems. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and ML Ops knowledge. We all know those technical questions can be tricky, so practice makes perfect!
✨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 Data Science Manager: Personalization & Recommendations
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for data science and personalisation shine through. We want to see how excited you are about enhancing customer engagement and making a real impact in the fashion retail space!
Highlight Relevant Experience: Make sure to showcase your experience with predictive models and recommendation systems. We’re looking for someone who can lead machine learning solutions, so don’t hold back on sharing your successes in this area!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so make it easy for us to see how your skills in Python and ML Ops align with what we need for the Data Science Manager 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 this exciting opportunity in our team!
How to prepare for a job interview at Ralph Lauren
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around predictive models and recommendation systems. Be ready to discuss your previous projects and how you've used Python and ML Ops to solve real-world problems.
✨Showcase Your Leadership Skills
As a Data Science Manager, you'll need to demonstrate your ability to lead teams. Prepare examples of how you've successfully managed projects or mentored team members in the past. Highlight your collaboration with marketing and engineering teams to show you're a team player.
✨Understand the Fashion Retail Landscape
Familiarise yourself with the fashion retail industry and its trends. Being able to discuss how data science can enhance customer engagement in this sector will set you apart. Think about how personalisation can impact customer experience and sales.
✨Prepare for Technical Questions
Expect some technical questions during the interview. Brush up on your machine learning algorithms and be prepared to explain your thought process when developing solutions. Practising coding challenges in Python can also help you feel more confident.
