Senior Data Scientist

The Department

Digital Experience and Innovation Department role is to build, cultivate and expand the digital ecosystem.  This involves acquiring and engaging customers, particularly focusing on acquisition and activation, wagering interest cultivation, fostering loyalty, and mitigating customer churn through the digital touch points and platforms.

The job holder reports to the Senior Data Scientist, is responsible for training, fine-tuning, and evaluating advanced AI and machine learning models to address key business needs, including large language models (LLMs), chatbots, and recommendation systems.  The role focuses on developing real-time, customer-facing AI solutions.

Key duties include helping set up training platforms and model frameworks; supporting data collection and labeling; training and evaluating AI models; deploying and monitoring models for concurrent real-time usage; and contributing to data pipelines, MLOps workflows, and data and model quality (validation, QA, and monitoring).  The job holder collaborates with IT and business teams to operationalize scalable AI solutions that enhance digital experiences and deliver measurable business value.

The Job

You will:

• AI and Machine Learning Engineering
  • Work closely with team members to define the technical scope and ensure alignment from requirements gathering through final delivery.
  • Build, train, and fine-tune advanced machine learning and AI models—including large language models (LLMs), generative AI, recommendation systems, chatbots—by leveraging both off-the-shelf models and developing custom solutions to deliver end-to-end solutions that enhance digital products and improve customer experience.
  • Assist with proofs of concept (PoCs), full-scale development, and operationalization of AI applications.
  • Demonstrate foundational knowledge of best practices across the model lifecycle—development, evaluation, validation, deployment, and monitoring.
  • Write efficient, maintainable, and scalable code in Python and other relevant languages to support all stages of model development, deployment, and integration.
  • Generate and analyze performance reports on deployed models, monitor end-to-end model performance, investigate anomalies, and propose improvements to maintain solution quality and maximize impact.
  • Help set up model training platforms (e.g., distributed training environments) and support data collection and labeling/tagging to prepare datasets for effective model training.
• Data Pipeline Engineering
  • Design and implement robust, scalable ETL/ELT pipelines to ingest, transform, and store data from source to model input.
  • Support QA, validation, and testing to help maintain data reliability, integrity, and compliance with governance standards.
  • Assist with deploying pipelines to production, ensuring smooth integration with analytics platforms and AI models.
  • Support continuous monitoring and maintenance of pipelines, proactively surfacing issues and helping ensure accurate, timely, and uninterrupted data delivery across the lifecycle.
• Workflow Design (MLOps & Data Pipelines)
  • Design MLOps and data-pipeline workflows that meet business objectives.
  • Assist in deploying AI solutions to production for robust, scalable performance.
  • Possess foundational understanding of best practices in AI infrastructure, security, and data management; research market trends, tools, and frameworks to stay current.
  • Help monitor, maintain, and optimize workflows for performance, scalability, and compliance with security and data governance standards.
• General Task
  • Ensures compliance with Responsible Gambling Policy (RGP) and all stipulated legal requirements pertaining to wagering, thereby protecting the integrity of the Club’s business
  • Undertakes other duties as assigned by Line Manager

About You

You should have

• Master’s degree in a quantitative discipline such as Data Science, Artificial Intelligence, Computer Science, Computer Engineering, or a related field.
• Strong computational background with production-level programming and scripting experience.
• Proven experience developing and deploying AI/ML models (e.g., LLMs, generative AI, recommendation systems, chatbots).
• Experience with model evaluation beyond accuracy (e.g., robustness, bias/fairness, safety, hallucination control) and with implementing guardrails, content filtering, and safety policies is a plus.
• Proven experience building real-time, low-latency AI systems.
• Experience with data engineering, including building and maintaining data pipelines, is a plus.
• Demonstrated ability to collaborate effectively with cross-functional teams (IT and business stakeholders).
• Experience setting up model training platforms, deploying models for concurrent use, and building end-to-end multi-model systems.
• Proficiency in data preparation, training/fine-tuning, and evaluation of AI/ML models.
• Experience with computer vision and speech (ASR and TTS) is a plus.
• Experience designing and analyzing experiments (A/B testing) and defining success metrics for ML features is a plus.
• Proficiency in Python for model development; familiarity with additional languages is a plus.
• Proficiency with SQL (or Spark SQL), Spark, and Kafka for data and model pipelines.
• Hands-on experience with AI/ML frameworks: PyTorch and/or TensorFlow (training and fine-tuning).
• Experience with LLMs and generative AI, including integration into end-to-end systems.
• Tools for model serving, deployment, and concurrency: Docker, Kubernetes, TensorFlow Serving, TorchServe (or equivalents).
• Knowledge of distributed training platforms/environments (e.g., multi-GPU, multi-node).
• Familiarity with data collection and labeling/tagging tools and workflows.

Terms of Employment

The level of appointment will be commensurate with qualifications and experience.

How to Apply

Please submit your resume with expected salary by clicking the Apply Now button.

We are an equal opportunity employer. Personal data provided by job applicants will be used strictly in accordance with the Club's notice to employees and prospective employees relating to the Personal Data (Privacy) Ordinance. A copy of which will be provided immediately upon request.