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- Tasks: Enhance recommendation systems and analyse user behaviour for actionable insights.
- Company: Leading entertainment publisher with a focus on innovation.
- Benefits: Competitive salary, flexible hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of personalised entertainment.
- Qualifications: Proficiency in Python, SQL, and strong mathematical skills required.
- Other info: Collaborative environment with a focus on creativity and teamwork.
The predicted salary is between 36000 - 60000 £ per year.
A leading entertainment publisher is seeking a Data Scientist to enhance recommendation systems and perform behavioral analytics. The ideal candidate must excel in Python and SQL, possess strong mathematical skills, and be familiar with machine learning frameworks.
This role involves integrating predictive models into recommendation strategies and analyzing user behavior to drive actionable insights. Collaboration with cross-functional teams is essential, making strong communication skills a must.
Data Scientist – Personalization & Recommendation Systems in London employer: Square Enix
Contact Detail:
Square Enix Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist – Personalization & Recommendation Systems in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in data science or at companies you're eyeing. A friendly chat can lead to insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python and SQL. Highlight any machine learning frameworks you've worked with. This is your chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex concepts in simple terms, as you'll need to collaborate with cross-functional teams. Remember, it's all about making those insights clear!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are proactive and engaged. Plus, it gives you a better chance of standing out in the application process.
We think you need these skills to ace Data Scientist – Personalization & Recommendation Systems in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and SQL expertise in your application. We want to see how you’ve used these skills in real projects, especially in relation to recommendation systems or behavioural analytics.
Math Matters: Don’t shy away from showcasing your mathematical skills! Whether it’s statistics or algorithms, let us know how you’ve applied these concepts in your previous work or studies.
Communication is Key: Since collaboration with cross-functional teams is a big part of the role, emphasise your communication skills. Share examples of how you’ve effectively worked with others to achieve common goals.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Square Enix
✨Brush Up on Your Technical Skills
Make sure you're comfortable with Python and SQL, as these are crucial for the role. Review key concepts in machine learning frameworks too, so you can confidently discuss how you've used them in past projects.
✨Showcase Your Analytical Mindset
Prepare to discuss specific examples of how you've performed behavioural analytics in previous roles. Be ready to explain your thought process and the impact your insights had on decision-making.
✨Communicate Clearly and Effectively
Since collaboration is key, practice explaining complex data concepts in simple terms. This will help demonstrate your strong communication skills and your ability to work with cross-functional teams.
✨Prepare Questions About the Company’s Goals
Research the company’s current recommendation systems and think about how you could enhance them. Prepare insightful questions that show your interest in their goals and how you can contribute to achieving them.