Data Scientist, Player Engagement & Growth

Data Scientist, Player Engagement & Growth

Full-Time 50000 - 70000 £ / year (est.) No working from home possible
Segment (Twilio)

At a Glance

  • Tasks: Build models to enhance player engagement and reduce churn using data-driven insights.
  • Company: Join Sony Interactive Entertainment, a leader in gaming innovation.
  • Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
  • Other info: Collaborative environment with exciting projects and career advancement potential.
  • Why this job: Make a real impact on player experiences with cutting-edge machine learning solutions.
  • Qualifications: Experience in data science, Python/SQL skills, and a passion for gaming.

The predicted salary is between 50000 - 70000 £ per year.

Sony Interactive Entertainment in London is seeking an accomplished Data Scientist to build models that drive churn reduction, personalised recommendations, and value optimization across PlayStation services.

You will work with cross‑functional teams to translate business questions into scalable ML solutions, using Python/SQL and modern ML tooling, with ownership from problem framing to solution delivery.

Data Scientist, Player Engagement & Growth employer: Segment (Twilio)

Join a forward-thinking company in Glenrothes or Livingston as a Principal Hardware Engineer, where you will be empowered to lead innovative power electronics designs and mentor a talented team. With a strong commitment to employee growth, competitive salaries, and a flexible working environment, we offer a culture that values collaboration and technical excellence. Enjoy unique benefits such as enhanced family policies, generous holiday allowances, and opportunities for community engagement through paid volunteering days.

Segment (Twilio)

Contact Details:

Segment (Twilio) Recruitment Team

We think you need these skills to ace Data Scientist, Player Engagement & Growth

Python
Communication Skills
SQL
Problem-Solving Skills
Automation
Data Engineering
Attention to Detail