Data scientist (AI Engineer)

Oxydata Software; Kuala Lumpur; On-site; MYR 60,000 - 90,000; Full time

Benefits offered by this job

Dynamic team environment

Cutting-edge technologies

Growth-oriented support

Job summary

Oxydata Software is looking for an experienced Data Scientist / AI Engineer in Kuala Lumpur to drive advanced machine learning solutions. The role involves developing and deploying models while collaborating with teams to fulfill business needs.

The ideal candidate possesses strong programming skills in Python, hands-on experience with ML frameworks, and operational knowledge of Google Cloud Platform. Join a dynamic team dedicated to leveraging AI-driven solutions.

Qualifications

• 2–5 years of experience building production machine learning systems.
• Experience with SQL feature pipelines and deployed serving endpoints.
• Ability to explain technical results clearly to non‑technical stakeholders.

Responsibilities

• Develop, improve, and deploy machine learning models and algorithms.
• Perform exploratory data analysis and validate hypotheses.
• Collaborate with cross-functional teams to translate business requirements.

Skills

Python programming

Machine learning frameworks (scikit-learn, TensorFlow, PyTorch)

SQL and NoSQL databases

Statistical knowledge

Google Cloud Platform (BigQuery, Vertex AI)

Education

Bachelor’s, Master’s, or PhD in Business, IT, Mathematics, Science, Engineering

Tools

Git

Jira

Confluence

G Suite

Job description

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‑B EATS, Neural Prophet, 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 impactful projects in a supportive and growth‑oriented environment.