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- Tasks: Lead the development of recommendation models for a major streaming service.
- Company: Dynamic streaming platform focused on innovation and user experience.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact on user experience through data-driven insights.
- Qualifications: Strong background in data science and experience with model deployment.
- Other info: Collaborative environment with mentorship opportunities and career advancement.
The predicted salary is between 43200 - 72000 £ per year.
A hands-on senior data science role focused on building and improving recommendation and personalisation models for a large-scale streaming product. This role owns delivery within a defined problem space — taking models from ideation through experimentation to production — while collaborating closely with engineering and product partners. There is scope to influence approach and mentor others, but the emphasis is on execution and impact.
Lead Data Scientist in London employer: Christy Media Solutions
Contact Detail:
Christy Media Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to folks in the data science community, especially those working in streaming products. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your recommendation and personalisation models. Use real-world examples to demonstrate your impact and execution capabilities — this will make you stand out!
✨Tip Number 3
Prepare for technical interviews by brushing up on your hands-on skills. Be ready to discuss your approach to taking models from ideation to production, and don’t forget to highlight your collaboration with engineering and product teams.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for talented data scientists like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Lead Data Scientist in London
Some tips for your application 🫡
Show Your Passion for Data Science: When writing your application, let your enthusiasm for data science shine through! Share specific examples of projects you've worked on, especially those related to recommendation and personalisation models. We want to see your hands-on experience and how it aligns with our mission.
Tailor Your Application: Make sure to customise your CV and cover letter for the Lead Data Scientist role. Highlight relevant skills and experiences that match the job description. We love seeing candidates who take the time to connect their background with what we’re looking for!
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language and avoid jargon unless it's necessary. We appreciate a well-structured application that makes it easy for us to see your qualifications and fit for the role.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the position. Plus, it shows you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Christy Media Solutions
✨Know Your Models Inside Out
Make sure you can discuss the recommendation and personalisation models you've worked on in detail. Be ready to explain your thought process from ideation to production, including any challenges you faced and how you overcame them.
✨Showcase Your Collaboration Skills
Since this role involves working closely with engineering and product partners, prepare examples of successful collaborations. Highlight how you’ve influenced decisions or mentored others in previous roles to demonstrate your teamwork abilities.
✨Prepare for Technical Questions
Brush up on your technical skills related to data science, especially in areas relevant to streaming products. Expect questions on algorithms, data manipulation, and model evaluation techniques, so be ready to dive deep into your expertise.
✨Demonstrate Impact and Execution
Be prepared to discuss specific projects where your work had a measurable impact. Use metrics to illustrate your success and show how your contributions led to improvements in performance or user experience.
