Data Scientist (3-year contract)

Global Sports Jobs Limited; Hong Kong; On-site; HKD 480,000 - 700,000; Full time

Benefits offered by this job

Competitive benefits package

Dynamic working environment

Development opportunities

Job summary

Global Sports Jobs Limited is seeking a data-focused professional to explore data, engineer features, and develop ML models within the Membership and Customer Excellence Division, delivering insights to deepen engagement across all customer segments.

You will build scalable pipelines, experiment with models, and productionise them with Docker/Kubernetes and MLflow, while monitoring performance and collaborating with team to drive personalised experiences across digital and physical touchpoints.

Qualifications

• Bachelor's degree in a relevant discipline (Business, Finance, Statistics, Data Science, Mathematics, IT).
• 5–8 years of experience in data analytics, statistics or related fields.
• Hands-on experience with relational databases and data transformation techniques.
• Experience with data visualisation, quantitative/financial modelling tools.

Responsibilities

• Collect, clean, process and explore large datasets from diverse sources.
• Support scalable data pipelines and ETL processes when needed.
• Identify and select features to improve model performance.
• Design, build, train and validate predictive and prescriptive models (regression, classification, clustering, NLP, recommendations).
• Design and run experiments to measure impact and iterate.
• Collaborate to productionise models using Docker, Kubernetes, MLflow or cloud services; establish monitoring pipelines.
• Proactively complete daily and weekly tasks assigned by the line manager.

Skills

Data analytics

Statistical analysis

Feature engineering

Model development

Experimentation

Deployment

Monitoring

Team collaboration

Education

Bachelor's degree in a relevant field

Tools

Docker

Kubernetes

MLflow

SQL

Cloud services

Job description

About the Role

The role focuses on data exploration, feature engineering, machine learning model development, experimentation, and model deployment and monitoring to solve real-world business problems. It sits within the Membership and Customer Excellence Division, which delivers world-class experiences and deepens engagement across all customer segments. The Division oversees clubhouses, racecourses and Off-Course Betting Branches, enhances member and owner value propositions, promotes interest in horse ownership and equestrian sports, and leads customer experience strategy across digital and physical touchpoints. It also manages data strategy and governance to build a unified view of customers, enabling more personalised and impactful interactions.

Key Responsibilities

• Collect, clean, process and explore large datasets from diverse sources to uncover patterns, trends and anomalies using statistical methods and visualisation tools.
• Support the development and maintenance of scalable data pipelines and ETL processes when needed.
• Identify, create and select relevant features to improve model performance and interpretability.
• Design, build, train and validate predictive and prescriptive machine learning models, such as regression, classification, clustering, NLP and recommendation systems, to solve real-world business problems.
• Design and implement rigorous tests and experiments to measure impact and iterate on solutions.
• Collaborate with teammates to productionise models using tools such as Docker, Kubernetes, MLflow or cloud services, and establish monitoring pipelines to track performance in production.
• Proactively take on and complete daily and weekly tasks assigned by the line manager.

Required Experience & Qualifications

• Bachelor's degree in a relevant discipline such as Business, Finance, Statistics, Data Science, Mathematics, or Information Technology.
• Minimum of 5-8 years of experience in data analytics, statistical analysis, or related fields.
• Hands-on experience with relational databases and data transformation techniques.
• Experience with data visualisation, quantitative and/or financial modelling tools and techniques.

Salary

• Competitive salary

Benefits & Perks

• Competitive benefits package
• Dynamic working environment
• Development opportunities