Overview

Location: London (Hybrid / Remote Options)

Salary: Competitive salary + Bonus + Benefits

Start Date: ASAP

About the Opportunity:

We are seeking a Data Scientist with 3–7 years of experience to join a fast-growing technology company operating in the gambling and gaming space.

This role is ideal for candidates who are either already experienced in the gambling sector or have a strong interest in applying data science within this industry. You’ll work on large, complex datasets to uncover behavioural patterns, build predictive models, and drive data-led strategies that directly influence product and business decisions.

What You’ll Be Doing

• Designing and deploying predictive models, machine learning solutions, and advanced statistical analyses
• Executing end-to-end data science workflows: from data acquisition and cleaning to modelling, validation, and deployment
• Applying statistical and ML techniques to identify insights from millions of behavioural data points
• Working closely with product and business teams to translate findings into actionable outcomes
• Measuring and improving platform and product performance through experimentation and analytics

What We’re Looking For

• 3–7 years’ experience in a Data Scientist or applied analytics role
• Proficiency in SQL and strong programming skills (Python, R, or similar)
• Hands-on experience with machine learning, predictive modelling, regression, hypothesis testing, and time-series analysis
• Ability to manage and deliver data projects independently as well as part of a team
• Strong communication skills for presenting technical insights to non-technical stakeholders
• Direct experience in the gambling / gaming industry
• Familiarity with cloud platforms (Azure, AWS, or GCP)
• Exposure to C# or other complementary programming languages

Culture & Benefits

• Flexibility: London HQ, remote, or hybrid (with reliable internet)
• Growth: Opportunity to shape projects in a high-impact, scaling business
• Autonomy: Freedom to choose tools and approaches to solve problems
• Culture: Collaborative, agile environment with minimal bureaucracy