Hello, I'm Marcus Liang.
Interact with the chatbot terminal below to learn more about my stack, or drag it around the screen!
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Experience
Business Analyst (Contract)
PhillipCapital
Key Responsibilities
- ▹ Collaborating on the development and enhancement of an automated trading management system that dynamically adjusts buy/sell trading thresholds based on creditability profile.
- ▹ Maintaining and optimizing existing RPA workflows, resolving operational bottlenecks to improve automation uptime and process efficiency across business functions.
Technologies Used
Tools: UiPath, Python (Polars), AI Models, Automation Frameworks
Business Analyst Intern
PhillipCapital
Key Responsibilities
- ▹ Developed an AI-integrated RPA framework to not only automate standard reporting but also parse data to extract actionable business insights.
- ▹ Spearheaded integration of mainstream AI tools with UiPath workflows, transforming static reports into dynamic, insight-driven analytics while saving up to 8 man-hours per reporting cycle.
- ▹ Gathered and synthesized feedback from key business stakeholders to iteratively refine prompt engineering and fine-tuning parameters, significantly improving the accuracy and quality of LLM outputs.
Technologies Used
Tools: UiPath, AI Models, Automation Frameworks
Data Scientist Intern
X-Star Technology
Key Responsibilities
- ▹ Engineered predictive repayment models using Random Forest and XGBoost to identify loaner's patterns and flag high-risk accounts, improving loan recovery efficiency.
- ▹ Included in developing machine learning models to analyse financial and behavioural data for credit risk assessment, increasing automated approval rates by ~80%; collaborated with cross-functional teams in Beijing.
- ▹ Architected interactive Power BI dashboards visualise repayment performance and track KPIs for dealer network, supporting decision-making.
- ▹ Executed financial Vintage Analysis grouped by Months on Books (MOB) to evaluate long-term loan performance and forecast future outcomes, such as early settlements.
Technologies Used
Languages: Python, SQL, JavaScript
Tools: MySQL Server, VS Code, Excel, Lark
Cross-Border E-Commerce Intern
Shopee
Key Responsibilities
- ▹ Automated key operational processes using Google Sheets and email notifications, reducing manual workload by up to 10 hours per week.
- ▹ Developed and implemented SQL queries to extract and analyse critical sales data, empowering data-driven decisions on customer behaviour and sales trends.
- ▹ Conducted in-depth analysis of monthly sales data to uncover trends and visualise insights through dynamic dashboards.
Technologies Used
Languages: Python, SQL, JavaScript
Tools: In-house query system, Google Sheets
Education
National University of Singapore
B.Sc. Business Analytics (Honours)
Specialization: Machine Learning.
Relevant Coursework: BT4221 Advanced Analytics with Big Data Technologies, BT4240 Machine Learning for Predictive Data Analytics, BT3017 Feature Engineering for Machine Learning, CS2040 Data Structures and Algorithms.
Ngee Ann Polytechnic
Diploma with Merit in Financial Informatics
Specialization: Financial Analytics.
Relevant Coursework: Deep Learning, Predictive Analytics, Applied Analytics.
Projects
Agentic Healthcare Analytics
Jan 2026 - Apr 2026
The Challenge
At the National Cancer Centre Singapore (NCCS), clinical experts often face significant delays when trying to validate medical hypotheses because they rely heavily on specialized data engineers to query and extract information from complex, highly-regulated healthcare databases.
The Objective
The objective was to bridge the gap between clinical expertise and data science by building an intelligent copilot that allows medical professionals to query complex datasets directly using natural language, without waiting for human intermediaries.
What I Built
Engineered a multi-agent AI workflow using LangGraph and DuckDB. The system uses ClinicalBERT and FAISS to ground medical terminology to actual database schemas, dynamically generating accurate SQL queries while enforcing strict Human-In-The-Loop (HITL) checkpoints.
The Result
Created an auditable, transparent analytics assistant that empowers clinicians to rapidly explore health data. This drastically reduces the turnaround time for hypothesis testing while preserving data security and exposing the analytical path for clinical review.
Skills Summary
🧠Generative AI & Deep Learning
LangChain, LangGraph, CrewAI, FAISS (Vector Stores), PyTorch, Ollama, OpenAI, NVIDIA NIM, Prompt Engineering
🤖Machine Learning
Supervised & Unsupervised Learning (Random Forest, XGBoost, Clustering), Scikit-learn, Model Validation (PSI)
🚀Deployment & Model Serving
Docker, FastAPI, Flask, MLFlow, DataOps, DevOps, GitHub (Version Control)
💻Programming Languages & Runtimes
Python, SQL (MySQL), Java, C#, R, JavaScript, Node.js
🗄️Data Engineering & Cloud
Databricks, Apache Spark, AWS, Snowflake, ETL Pipelines
📊Data Analytics & BI
Pandas, NumPy, Polars, Power BI (DAX), Tableau, Matplotlib, Vintage Analysis
⚙️Automation & Tools
UiPath, Power Automate, Advanced Excel
💡Core Competencies
Analytical Problem-Solving, Continuous Learning, Adaptability, Communication, Teamwork, Time Management
Let's Connect.
I am always open to discussing data strategy, open-source projects, or the latest in cloud tech. Feel free to reach out via LinkedIn or email me 😀