Job Description

Data Science Intern

Department: Technology

Employment Type: Internship

Location: Malta

Reporting To: Jake Bonnici

Key Responsibilities

• Improving and optimising our Game Recommendation Engine (GRE) to deliver personalised player experiences and increase engagement.
• Developing customer segmentation solutions that help operators better understand their players and tailor their offerings.
• Enhancing Anti-Money Laundering (AML) systems using advanced machine learning and deep learning techniques.
• Building and improving customer churn prediction models to help operators identify at-risk players and improve retention.
• Exploring innovative AI solutions that drive customer engagement, operational efficiency, and business growth.
• Building, testing, and deploying machine learning models in a production environment.
• Analysing large-scale datasets to uncover insights and opportunities for optimisation.

• How commercial Data Science products are designed, developed, and maintained.
• Best practices for machine learning experimentation, model deployment, and monitoring.
• How to translate business challenges into data-driven solutions.
• The end-to-end lifecycle of AI and Data Science projects, from ideation and experimentation through to production.
• How Data Science contributes to player engagement, customer retention, fraud prevention, and commercial growth.
  
  

• Machine Learning & Deep Learning frameworks
• MLflow
• Sql
• Python
• Real-time data pipelines
  
  

• Present your work to technical and business stakeholders during quarterly team showcases.
• Collaborate with experienced professionals in a supportive and innovative environment.
• Gain valuable industry experience while contributing to products used by operators around the world.
  
  

Requirements

• Currently enrolled in, or recently graduated from, a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or another quantitative field.
• Strong proficiency in Python, including experience with libraries such as Pandas, NumPy, and Scikit-learn.
• Basic SQL skills for data extraction, transformation, and analysis.
• A solid understanding of statistics, machine learning concepts, and data analysis techniques.
• Curiosity and a willingness to experiment, learn, and solve complex problems.
• Strong communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
• A passion for Data Science, AI, and building solutions that create real business value.

Benefits

• Great career development opportunities
• Hybrid working model
• International Health Insurance
• Health and Wellbeing Package (350 EUR per year)
• Birthday Day Off
• Me Time - 1 day off per year