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- Tasks: Build models for hyper-personalisation and consult with executive teams.
- Company: Leading global eCommerce company with a focus on innovation.
- Benefits: Flexible work, competitive benefits, and opportunities for personal growth.
- Why this job: Join a dynamic team and shape customer experiences with cutting-edge technology.
- Qualifications: Expertise in machine learning, deep learning, and programming languages like Python and Java.
- Other info: Collaborative environment with a focus on cross-functional teamwork.
The predicted salary is between 36000 - 60000 £ per year.
A leading global eCommerce company is seeking a Lead Data Scientist to build models for hyper-personalisation of customer experiences while consulting with executive teams. This hands-on role requires expertise in machine learning, deep learning, and programming languages like Python and Java.
The ideal candidate should be comfortable with data analytics pipeline design, possess advanced mathematics skills, and work effectively in cross-functional teams.
This position offers flexibility, a competitive benefits package, and the opportunity for personal growth.
Lead Data Scientist - Hybrid ML & Personalization Leader employer: match digital.
Contact Detail:
match digital. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist - Hybrid ML & Personalization Leader
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. 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 and data analytics work. This will give potential employers a taste of what you can do and set you apart from the competition.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in hyper-personalisation. Practice common interview questions and be ready to discuss your experience with Python, Java, and model building.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Lead Data Scientist - Hybrid ML & Personalization Leader
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your expertise in machine learning and deep learning. We want to see how you’ve used Python and Java in your previous roles, so don’t hold back on those details!
Tailor Your Application: Customise your CV and cover letter to reflect the job description. We’re looking for someone who can build models for hyper-personalisation, so make it clear how your experience aligns with that.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it’s necessary. Let us see your thought process without getting lost in complex language.
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!
How to prepare for a job interview at match digital.
✨Know Your Tech Inside Out
Make sure you brush up on your machine learning and deep learning concepts. Be ready to discuss specific algorithms you've implemented and the programming languages you’re proficient in, especially Python and Java. This will show that you’re not just familiar with the tech but can also apply it effectively.
✨Showcase Your Problem-Solving Skills
Prepare to discuss past projects where you’ve built models for hyper-personalisation or similar tasks. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting how you approached challenges and what impact your solutions had on customer experiences.
✨Understand the Business Context
Since this role involves consulting with executive teams, it’s crucial to understand the eCommerce landscape. Research the company’s current strategies and think about how your data science expertise can contribute to their goals. This will demonstrate your proactive approach and alignment with their vision.
✨Be Ready for Team Dynamics
This position requires collaboration across various teams, so be prepared to discuss your experience working in cross-functional environments. Share examples of how you’ve successfully communicated complex data insights to non-technical stakeholders, showcasing your ability to bridge the gap between data science and business needs.
