Data Scientist

Arise

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.

Posted 8/4/2026full-timeRemote • 🇲🇹 MaltaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and prototyping machine learning and deep learning models for computer vision tasks, with a strong foundation in Python and frameworks like PyTorch or TensorFlow. Capable of collaborating with cross-functional teams to translate business objectives into effective applied ML solutions.

Highest-signal resume keywords

Machine Learning Model DevelopmentDeep Learning Frameworks (PyTorch, TensorFlow)Computer Vision (Object Detection, Image Classification, Tracking)Model Evaluation and BenchmarkingCollaboration with ML Engineers

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningPythonComputer VisionModel EvaluationData VersioningLarge Dataset ManagementAblation StudiesBenchmarkingHypothesis Testing

Tools & Technologies

AzureAWSGCPDockerCI/CD PipelinesHugging Face TransformersVision TransformersSelf-Supervised LearningGenerative AILLM Frameworks

Industry Keywords

Electrical EngineeringComputer ScienceQuantitative DisciplineGamingIGamingE-commerceConsumer-Facing Applications

Tech Stack

Tools & technologies

AWSAzureDockerGoogle Cloud PlatformPythonPyTorchTensorflow

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

Master's degree in Electrical Engineering, Computer Science, or a related quantitative discipline
Hands-on experience developing ML and deep learning models, including demonstrated computer vision work
Strong proficiency in Python and a deep learning framework such as PyTorch or TensorFlow
Experience with computer vision models for object detection, image classification, and tracking
Solid grounding in deep learning, traditional computer vision, and classical ML
Experience with benchmarking, ablation studies, and structured evaluation of competing approaches
Experience working with large, complex datasets
Experience collaborating with ML Engineers to bring models into production is nice to have
Experience with Azure, AWS, or GCP for ML training and deployment is nice to have
Familiarity with Docker and CI/CD pipelines is nice to have
Experience with Hugging Face Transformers, vision transformers, or self-supervised / representation learning is nice to have
Exposure to generative AI, including prompt engineering, RAG, LLM frameworks, or LLM fine-tuning is nice to have
Background in gaming, iGaming, e-commerce, or other consumer-facing applications at scale is nice to have

Benefits

Comp & perks

Opportunities for professional and personal development
Collaborative, cross-functional environment with visible impact
End-to-end involvement from research and prototyping through to production
Work on substantial, real-world computer vision and deep learning problems at scale