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For Companies At a Glance
- Tasks: Build recommendation systems and analyse user behaviour to enhance gaming experiences.
- Company: Leading gaming company in Greater London with a passion for innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact on user engagement in gaming.
- Qualifications: Proficiency in Python and SQL, with a strong foundation in applied mathematics.
- Other info: Collaborate with experts to integrate predictive models and drive marketing success.
The predicted salary is between 43200 - 72000 £ per year.
A leading gaming company in Greater London is seeking a passionate Data Scientist to build recommendation systems and conduct deep behavioral analytics. This role requires proficiency in Python and SQL, a strong foundation in applied mathematics, and experience with recommender system techniques.
The ideal candidate will work collaboratively with Forecast experts to integrate predictive models and enhance marketing interventions. Join a dynamic team committed to delivering unforgettable experiences.
Data Scientist, Recommender Systems & Personalization employer: Square Enix
Contact Detail:
Square Enix Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist, Recommender Systems & Personalization
✨Tip Number 1
Network like a pro! Reach out to people in the gaming industry, especially those working with recommendation systems. A friendly chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python and SQL, especially any work related to recommender systems. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for interviews by brushing up on applied mathematics and behavioural analytics. Be ready to discuss how you've used these skills in past projects, as this will show you're the perfect fit for the role.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Data Scientist, Recommender Systems & Personalization
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for data science and gaming shine through. We want to see how your passion aligns with our mission to create unforgettable experiences!
Highlight Relevant Skills: Make sure to showcase your proficiency in Python and SQL, as well as your experience with recommender systems. We’re looking for candidates who can hit the ground running, so don’t hold back on your technical skills!
Collaborative Spirit: Since this role involves working closely with Forecast experts, emphasise any past experiences where you’ve collaborated effectively. We value teamwork, so let us know how you can contribute to our dynamic team!
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. Don’t miss out!
How to prepare for a job interview at Square Enix
✨Know Your Tech
Make sure you're well-versed in Python and SQL. Brush up on your coding skills and be ready to discuss specific projects where you've used these languages, especially in building recommendation systems.
✨Showcase Your Math Skills
Since a strong foundation in applied mathematics is crucial, prepare to explain how you've applied mathematical concepts in your previous work. Be ready to tackle any technical questions that might come your way.
✨Collaborative Spirit
This role involves working closely with Forecast experts, so highlight your teamwork experience. Share examples of how you've successfully collaborated on projects and integrated different models or techniques.
✨Passion for Gaming
As you're applying to a leading gaming company, express your enthusiasm for the industry. Share your favourite games and how they inspire your work in data science, particularly in enhancing user experiences through personalisation.
