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- Tasks: Lead the design and deployment of advanced machine learning solutions in eCommerce.
- Company: Join a fast-scaling retail powerhouse known for its data-driven approach.
- Benefits: Competitive salary up to £75,000, hybrid work model, and career growth opportunities.
- Why this job: Make a real impact on commercial performance through innovative data analytics.
- Qualifications: Experience in data science and machine learning, with strong leadership skills.
- Other info: Dynamic and collaborative environment with a focus on innovation.
The predicted salary is between 45000 - 105000 £ per year.
Leicester, UK (Hybrid)
Up to £75,000 DOE
iO Associates are aligned with one of the UK's most recognised and fast-scaling retail powerhouses, operating at significant scale within a highly data-driven eCommerce environment where analytics directly shapes commercial performance.
This role will lead the design and deployment of advanced machine learning solutions focused on...
Lead Data Scientist - eCommerce in Leicester employer: Confidential
Contact Detail:
Confidential Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist - eCommerce in Leicester
✨Tip Number 1
Network like a pro! Reach out to people in the eCommerce and data science fields on LinkedIn. A friendly message can go a long way, and you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and data analysis work. This will give potential employers a taste of what you can bring to the table, especially in a data-driven environment.
✨Tip Number 3
Prepare for those interviews! Brush up on common data science interview questions and be ready to discuss your past experiences. We recommend practising with a friend or using mock interview platforms to build your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Lead Data Scientist - eCommerce in Leicester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience in eCommerce and any advanced machine learning projects you've led. We want to see how your skills align with our data-driven environment!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science in eCommerce and how you can contribute to our team. Let us know what excites you about working with us at StudySmarter.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work that demonstrate your expertise in machine learning and analytics. We love seeing real-world applications of your skills.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. We can't wait to hear from you!
How to prepare for a job interview at Confidential
✨Know Your Data Science Fundamentals
Brush up on your core data science concepts, especially those related to machine learning and analytics. Be prepared to discuss how you've applied these principles in real-world scenarios, particularly in eCommerce settings.
✨Showcase Your Problem-Solving Skills
Prepare to tackle case studies or hypothetical scenarios during the interview. Think about how you would approach a specific data challenge in an eCommerce context, and be ready to explain your thought process clearly.
✨Familiarise Yourself with the Company’s Data Strategy
Research the company’s current data initiatives and how they leverage analytics for commercial performance. This will not only show your interest but also help you align your answers with their goals and challenges.
✨Prepare Questions That Matter
Have insightful questions ready that demonstrate your understanding of the role and the industry. Ask about their current projects, team dynamics, or future data strategies to show you're genuinely interested in contributing to their success.
