Mark Enhan Yong, CFA, FRM

Built and operate a private AI platform (288GB VRAM) focused on secure model deployment, local LLM inference, and retrieval-driven analytics workflows. Setup designed to support applied AI use cases in environments with high data sensitivity and infrastructure ownership requirements. - Built self-improving system with agents controlling deployment of Docker stacks to Proxmox. - Deployed local inference engines (vLLM, SGLang, llama.cpp) with OpenAI-compatible APIs; tuned performance across quantization, batching, and long-context workloads. - Implemented retrieval-augmented generation (RAG) pipelines integrating embeddings, vector storage, and controlled search to support research and knowledge workflows. - Developed agent-style interfaces and conversational tools for analytics and decision support across structured and unstructured datasets. - Designed secure remote access, environment isolation, and operational runbooks aligned to production-style AI deployment in regulated environments. Focus areas: Applied AI for financial workflows · Private LLM deployment · Cost-efficient model serving

- Led a team of 20+ data scientists and analysts across SG, MY, ID, and IN - Developed and implemented group-wide data strategy aligned with business growth and risk mitigation - Built up enterprise data warehouse analytics layer and led BI migration from Sisense to Qlik Sense - Oversaw development of monthly financial and management reporting systems with historical tracking - Integrated payments and new credit lines products into core analytics stack post-CardUp acquisition - Established RBAC and data governance frameworks with Legal, Compliance, and IT Security - Developed credit risk models across markets (microlending AUC >75%, term loans in SG/MY/ID) - Spearheaded development of collateral system, unlocking ~$100M in new lending potential - Provided insights and dashboards to country teams and executives to drive growth and efficiency - Automated key reporting and finance workflows using Python, SQL, and Qlik

Senior Officer - Vice President - Acted as Scrum Master for a cross-functional team delivering management reporting in Power BI - Built KPI dashboards for senior management; conducted training for 100+ Finance users in Qlik Sense - Performed customer analytics and created segmentation models for Group Retail - Enhanced and maintained cost allocation engine using Impala and Python in collaboration with external consultants

- Deep Learning, Machine Learning, Natural Language Processing, Time Series, Data Engineering - Python, R, Google Cloud, Docker, Spark, Kafka, Hadoop, Git - As for Advanced Data Sci Stats, Applied Machine Learning, NLP using Deep Learning

Graduated with Distinction - Vice-Chancellor’s List ( Top 1% of all Curtin students) - Awarded Commendations (from Pro Vice-Chancellor and Head of School of Economics and Finance) - High Distinction course weighted average - High Distinctions in all Finance subjects (including Instruments and Markets, Quantitative Techniques, and Derivatives)