Data scientist (AI Engineer)

Job Openings Data scientist (AI Engineer)

About The Job 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 forecasting and regression challenges, including lag feature leakage, target leakage in cross-validation, high-cardinality categorical handling, and trade-offs between MAE, MAPE, and RMSE.
• Ability to interpret models using methods such as SHAP, partial dependence, and residual diagnostics.
• Ability to work under pressure and adapt to change.
• Ability to balance speed, reliability, and interpretability.
• Ability to explain technical results clearly to non-technical stakeholders.

Nice-to-have

• Experience with deep learning for tabular and time-series problems such as TFT, N-BEATS, NeuralProphet, TabPFN, and Chronos.
• Experience with AutoML tools such as PyCaret for rapid baselining.
• Golang experience for performance-critical services.
• Experience with LLM-based or agentic tooling such as LangGraph, MCP servers, prompt engineering for structured outputs, and evaluation harnesses for LLM systems.
• Familiarity with design thinking methods.
• Experience with open-source tools and libraries.
• Strong monitoring discipline, including drift detection and model performance tracking in production.

Why Join Us

• Join a dynamic and innovative team where your expertise will directly influence business outcomes and the adoption of AI-driven solutions.
• Work with cutting-edge technologies, collaborate with talented professionals, and contribute to im…