Data Scientist, CLV & Next-Best Action Personalisation (Hybrid)

Data Scientist, CLV & Next-Best Action Personalisation (Hybrid)

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
PlayStation

At a Glance

  • Tasks: Build models to enhance player engagement using modern machine learning techniques.
  • Company: Join PlayStation, a leader in gaming innovation and collaboration.
  • Benefits: Enjoy hybrid working, extensive benefits, and growth opportunities.
  • Other info: Exciting opportunity for career growth in a collaborative environment.
  • Why this job: Make a real impact on player engagement strategies in a dynamic field.
  • Qualifications: Strong analytical skills with experience in Python and SQL.

The predicted salary is between 60000 - 80000 £ per year.

PlayStation is seeking a motivated Data Scientist to join its CLV & Next Best Action team. You will build models to understand and influence player engagement and value, using modern machine learning techniques.

The ideal candidate will possess strong analytical skills and a background in predictive modeling with experience in Python and SQL.

PlayStation offers a collaborative work environment with opportunities for growth in a dynamic field. The position includes hybrid working and extensive benefits, providing an exciting opportunity to significantly impact our player engagement strategies.

Data Scientist, CLV & Next-Best Action Personalisation (Hybrid) employer: PlayStation

PlayStation is an exceptional employer, offering a vibrant and collaborative work culture that fosters innovation and creativity. With a focus on employee growth, the company provides extensive benefits and hybrid working options, allowing you to thrive in a dynamic environment while making a meaningful impact on player engagement strategies.

PlayStation

Contact Details:

PlayStation Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Scientist, CLV & Next-Best Action Personalisation (Hybrid)

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like PlayStation!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist, CLV & Next-Best Action Personalisation (Hybrid) at PlayStation.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like PlayStation.

Apply Directly through Our Website

When you find a suitable opening like Data Scientist, CLV & Next-Best Action Personalisation (Hybrid) at PlayStation, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Scientist, CLV & Next-Best Action Personalisation (Hybrid)

Analytical Skills
Predictive Modeling
Machine Learning Techniques
Python
SQL
Player Engagement Strategies
Collaboration

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at PlayStation, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at PlayStation. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at PlayStation

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at PlayStation!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.