Data Scientist

• Design and prototype ML and deep learning models, primarily for computer vision tasks including object detection, classification, and tracking
• Frame business problems as testable hypotheses and develop proofs-of-concept to validate them
• Evaluate and benchmark competing model architectures and pre-trained models
• Collaborate with ML Engineers to scale validated prototypes into production systems and remain engaged through deployment
• Track experiments, manage model and data versioning, and define objective evaluation metrics
• Work with product, engineering, and business teams to turn objectives into applied ML solutions

Data Scientist applying computer vision and deep learning to large-scale iGaming products at ARRISE

Data Scientist developing applied computer vision and deep learning models for ARRISE’s large-scale iGaming products.
Prototyping research solutions, benchmarking architectures, and collaborating on production deployment.

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

Data Science Intern working on business challenges in the fast-paced iGaming industry

Data Science Intern

Data Science Intern developing data-driven solutions in the iGaming industry. Collaborating with experienced Data Scientists and Engineers to deliver impactful projects.

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Data Scientist

Data Science Intern