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- Tasks: Develop predictive models to enhance user personalisation and engagement.
- Company: Leading financial technology service in the UK with a collaborative culture.
- Benefits: Flexible working options and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact on user experience.
- Qualifications: Proficiency in Python, SQL, and strong statistical knowledge.
- Other info: Exciting role in a fast-paced environment with great career potential.
The predicted salary is between 36000 - 60000 £ per year.
A leading financial technology service in the UK is seeking a Data Scientist for their Data & Analytics team. The candidate will be responsible for managing the development of predictive models aimed at enhancing user personalization and engagement.
Essential skills include proficiency in Python and SQL, as well as a strong understanding of statistical methods and machine learning techniques.
The role promotes a collaborative environment with flexible working options available.
Global Targeting Data Scientist - Personalisation in London employer: ClearScore
Contact Detail:
ClearScore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Global Targeting Data Scientist - Personalisation in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working in data science or fintech. A friendly chat can lead to valuable insights and even job referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and projects using Python and SQL. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on statistical methods and machine learning techniques. Be ready to discuss how you've applied these in real-world scenarios, as this will demonstrate your expertise and problem-solving abilities.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Global Targeting Data Scientist - Personalisation in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your proficiency in Python and SQL right from the get-go. We want to see how your skills align with the role, so don’t hold back on showcasing your experience with predictive models and machine learning techniques!
Tailor Your Application: Take a moment to customise your application for this specific role. Mention how your background in data science can enhance user personalisation and engagement, as that’s what we’re all about at StudySmarter!
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and enthusiasm for the position.
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 role. We can’t wait to hear from you!
How to prepare for a job interview at ClearScore
✨Know Your Tech Inside Out
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss specific projects where you've used these languages, and think about how you applied statistical methods and machine learning techniques to solve real problems.
✨Showcase Your Predictive Modelling Experience
Prepare to talk about your experience with developing predictive models. Have examples ready that demonstrate how your work has enhanced user personalisation and engagement. This will show that you understand the role's core responsibilities.
✨Emphasise Collaboration Skills
Since the role promotes a collaborative environment, be prepared to discuss how you've worked effectively in teams. Share examples of how you’ve contributed to group projects and how you handle feedback and differing opinions.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team dynamics, the tools they use for data analysis, or how they measure the success of their predictive models. This shows your genuine interest in the role and the company.
