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- Tasks: Lead technical strategy and architecture for ML in recommendation systems.
- Company: Join a forward-thinking company shaping the future of personalisation.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Why this job: Be a key player in influencing ML roadmaps and tackling challenging problems.
- Qualifications: Proven experience in machine learning and strong leadership skills.
- Other info: Dynamic role with significant impact on multiple teams and projects.
The predicted salary is between 54000 - 84000 £ per year.
A principal-level individual contributor role with responsibility for technical strategy, standards, and architecture across recommendation and personalisation systems. This role sets the direction for how ML is designed, evaluated, and deployed across multiple teams. You’ll act as a technical authority, influencing long-term ML roadmaps, platform decisions, and best practices while still staying close to the hardest problems.
Prinicipal Data Scientist in City of London employer: Christy Media Solutions
Contact Detail:
Christy Media Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Prinicipal Data Scientist in City of London
✨Tip Number 1
Network like a pro! Reach out to current or former employees in similar roles on LinkedIn. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Showcase your expertise! Prepare a portfolio of your past projects, especially those related to ML strategies and architectures. This will help you stand out during interviews.
✨Tip Number 3
Stay updated with the latest trends in ML and data science. Share your insights during interviews to demonstrate your passion and knowledge in the field.
✨Tip Number 4
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 Prinicipal Data Scientist in City of London
Some tips for your application 🫡
Showcase Your Expertise: When applying for the Principal Data Scientist role, make sure to highlight your technical skills and experience in ML. We want to see how you've influenced strategies and standards in your previous roles, so don’t hold back!
Tailor Your Application: Take a moment to customise your CV and cover letter for this specific role. We love seeing candidates who understand our mission and can articulate how their background aligns with our goals in recommendation and personalisation systems.
Be Clear and Concise: In your written application, clarity is key! We appreciate straightforward language that gets to the point. Avoid jargon unless it’s necessary, and make sure your passion for tackling complex problems shines through.
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Christy Media Solutions
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially around recommendation systems and personalisation. Be ready to discuss how you would approach designing, evaluating, and deploying ML models, as this will show your technical authority in the field.
✨Showcase Your Strategic Thinking
Prepare to talk about your experience with setting technical strategies and standards. Think of specific examples where you've influenced ML roadmaps or platform decisions, and be ready to explain your thought process behind those decisions.
✨Demonstrate Problem-Solving Skills
Expect to tackle some challenging problems during the interview. Practice articulating your problem-solving approach clearly, focusing on how you break down complex issues and collaborate with teams to find effective solutions.
✨Engage with the Interviewers
Don’t just wait for questions; engage with your interviewers. Ask insightful questions about their current ML challenges and how they envision the future of their recommendation systems. This shows your genuine interest and helps you assess if the role aligns with your goals.
