Data Scientist
We are looking for an experienced Data Scientist to join our growing team in Kuala Lumpur. You will work in a hybrid mode, independently advising on AI application areas, designing and building end-to-end ML pipelines and integrating AI solutions into scalable software products. If you thrive in a fast-paced, product-oriented Agile environment and enjoy working closely with both technical teams and business stakeholders to turn data into measurable impact, we want to hear from you.
Responsibilities
- Independently identify high-impact AI opportunities, capture business requirements, and translate them into robust mathematical models
- Oversee the entire data lifecycle, from conceptualizing labeling processes and performing EDA to advanced statistical analysis
- Select and implement ML and semantic models, validating approaches against current scientific literature to ensure best-in-class performance
- Design and implement automated MLOps pipelines for model creation, QA and deployment via RESTful APIs (e.g., FastAPI, Flask)
- Architect and implement scalable infrastructure to seamlessly integrate AI components into production-grade software products
- Ensure all AI solutions adhere to global data privacy standards, AI ethics and IT security regulations
- Partner with System Engineers and Product teams in an Agile (Scrum/Kanban) framework to deliver measurable value
- Distill complex methodologies into clear, actionable insights for both technical peers and non-technical stakeholders
Requirements
- Hands-on experience in Data Science or Machine Learning Engineering roles
- Bachelor’s degree in Computer Science, Applied Mathematics, Engineering, or a related quantitative field
- Strong proficiency in Python and SQL
- Demonstrated experience with Microsoft Azure (primary focus); AWS or GCP experience is highly valued
- Proven track record in at least two ML domains (e.g., Forecasting, NLP, Computer Vision, Anomaly Detection, or LLM applications)
- Practical experience in model selection, training and deployment within scalable, automated production pipelines
- Comfortable working in product-oriented teams, contributing to a culture of rapid iteration and cross-functional transparency
- Strong awareness of data security and AI compliance standards
Nice to have
- Expertise with MLflow or other MLOps frameworks
- Familiarity with LLM frameworks (e.g., LangChain), multi-agent systems, or advanced prompt engineering
- Professional certifications in Data Architecture or Cloud Engineering
