Data scientist (AI Engineer)

Data Scientist / AI Engineer Location: Kuala Lumpur, Malaysia Work Mode: Onsite Employment type: Permanent Our client is a leading digital travel and lifestyle platform in Asia, connecting millions of users to a wide range of offerings. They are a prominent player in the travel industry, recognized for their innovative approach and extensive network. The company operates with a significant global presence, serving a vast customer base across numerous countries. They are committed to providing seamless and accessible travel experiences. We are seeking an experienced Data Scientist / AI Engineer to drive the development and deployment of advanced machine learning solutions. Responsibilities Develop, improve, and deploy machine learning models and algorithms to optimize business processes and outcomes. Perform exploratory data analysis and validate hypotheses to inform model development. Build optimization, predictive, and statistical models to extract insights and estimate unknown outcomes. Design and implement SQL feature pipelines and manage deployed serving endpoints. Utilize cloud platforms, particularly Google Cloud Platform (BigQuery, Vertex AI), for model deployment and automation. Collaborate with cross-functional teams to translate business requirements into technical solutions. Apply statistical knowledge to business and finance-related use cases. Interpret and communicate model results using techniques such as SHAP, partial dependence, and residual diagnostics. Maintain code quality through version control, code review, and documentation practices. Work with productivity tools such as G Suite, Git, Jira, and Confluence to ensure efficient project management and collaboration. Adapt to changing priorities and work effectively under pressure while balancing speed, reliability, and interpretability. Requirements Must-have: Bachelor’s, Master’s, or PhD degree in Business, IT, Mathematics, Science, Engineering, or a related discipline. Up to 4 years of relevant experience beyond first degree. 2–5 years of experience building production machine learning systems beyond notebooks and Kaggle competitions. Strong Python programming skills. Hands-on experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch. Hands-on experience with Google Cloud Platform, especially BigQuery and Vertex AI. Strong understanding of machine learning algorithms such as XGBoost, LightGBM, neural networks, and decision trees. Good working knowledge of productivity tools such as G Suite, Git, Jira, and Confluence. Experience in building optimization, predictive, and statistical models. Good applied statistical knowledge, especially in business and finance-related use cases. Experience with SQL and NoSQL databases. Experience with SQL feature pipelines and deployed serving endpoints. Experience with Git-based workflows, CI/CD practices, and code review discipline. Understanding of…