At a Glance
- Tasks: Apply causal inference to enhance Customer Lifetime Value through data analysis and experimentation.
- Company: Join Sony Interactive Entertainment, a leader in gaming and entertainment innovation.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with diverse teams and exciting projects.
- Why this job: Make a real impact on customer insights and decision-making in the gaming industry.
- Qualifications: Strong stats background, Python and SQL skills, and experience with causal methods required.
The predicted salary is between 60000 - 80000 £ per year.
Sony Interactive Entertainment is seeking a data-focused professional to apply causal inference to understand and improve Customer Lifetime Value (CLV).
You will design experiments, analyse large datasets, and work with cross-functional teams to embed insights into decision-making.
The role requires strong statistics, Python and SQL proficiency, and experience with causal methods such as PSM, Di D, and causal forests.
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Causal Data Scientist - Incremental Player Value employer: Sony Interactive Entertainment
Sony Interactive Entertainment is an exceptional employer, offering a vibrant work culture that fosters creativity and collaboration in the heart of London. Employees benefit from competitive compensation, flexible hybrid working arrangements, and ample opportunities for professional growth within a leading global brand. Join us to make a meaningful impact in a dynamic environment where your contributions are valued and recognised.
Contact Details:
Sony Interactive Entertainment Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Causal Data Scientist - Incremental Player Value
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We think you need these skills to ace Causal Data Scientist - Incremental Player Value
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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