Data Scientist & AI Engineer
Building end-to-end intelligent systems across the full data stack—from infrastructure and pipelines to machine learning models and GenAI applications. I transform complex data challenges into scalable, production-ready solutions that drive business impact.
With 4+ years of experience spanning fintech, media, and education technology, I specialize in architecting and deploying AI/ML solutions that solve real-world problems. My approach combines full-stack data capabilities with cutting-edge GenAI to build systems that are intelligent, scalable, and business-aligned.
I excel across the entire data lifecycle—designing robust data platforms and pipelines, generating data insights, developing machine learning models (from traditional ML to LLMs), implementing MLOps best practices, and creating GenAI-powered applications. Whether it's building recommendation systems, RAG-based chatbots, or internal AI agents for analytics, I focus on delivering production-grade solutions with proper monitoring, CI/CD, and cloud infrastructure.
Currently at Tupai AI, I own the complete data stack for an education tech platform, where I've built everything from data infrastructure to an internal AI agent that democratizes data access across the entire company.
Bachelor of Computer Science (Hons) with Specialization in Data Science
Multimedia University, Malaysia (2018–2021)
Company-wide AI agent enabling non-technical teams to query and analyze data through natural language. Handles complex analytics requests, generates insights, creates dashboards, and democratizes data access across the organization.
Architected complete data infrastructure for education tech platform including data pipelines, ML model deployment, recommendation systems for personalized mathematics learning, and analytics dashboards.
Personalized mathematics learning system combining Bayesian Knowledge Tracing with traditional ML to model student knowledge states. Identifies weak points in real-time and generates tailored learning plans, optimizing educational pathways based on individual performance patterns.
End-to-end multi-turn question-answering chatbot with Retrieval-Augmented Generation. Deployed on GCP using FastAPI and Haystack, integrated across multiple channels including WhatsApp for enhanced customer engagement.
Geolocational hyper-personalization system that drove substantial increases in organic user engagement across multiple products using neural networks and location-based targeting.
Migrated on-premise ML models to GCP Vertex AI with enhanced monitoring, observability, and CI/CD integration using Kubeflow and Docker for improved scalability and automation.
Led research and POC development for multiple client projects, identifying ML use cases and translating business problems into AI solutions. Managed end-to-end project lifecycles from consultation through deployment.
Led migration of data team's ETL pipelines and dbt SQL transformations from AWS Redshift to Snowflake. Migrated workflows in Airflow to optimize for Snowflake's architecture, ensuring zero downtime and improved query performance.
Designed and executed multiple A/B testing experiments to enhance Natural Language Understanding models for customer support. Analyzed unstructured text data to identify pain points and optimize model performance, resulting in reduced operational costs.
AI chatbot on Discord that provides personalized learning experiences with LaTeX rendering for mathematical calculations using Haystack and the Discord API.
Fine-tuned ResNet50 model on 1M+ images for e-commerce product classification, automatically categorizing products up to 3 levels deep using transfer learning.
NLP project mining millions of Steam game reviews, performing data validation and preprocessing, then applying neural networks and traditional ML for aspect-based sentiment analysis.
I'm open to collaborations, opportunities, and conversations about AI, ML, and data engineering. Feel free to reach out via email or connect with me on LinkedIn.