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
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, Machine Learning for Predictive Data Analytics.
Ngee Ann Polytechnic
Diploma with Merit in Financial Informatics
Specialization: Financial Analytics.
Relevant Coursework: Deep Learning, Predictive Analytics, Applied Analytics.
Projects
Beijing House Market Analysis
Mar 2024 – Apr 2024
Analyzed Beijing housing data (2011–2017) to provide actionable business insights regarding market risks and investment viability.
Technologies & Stack
Skills Summary
Generative AI & Deep Learning
LangChain, LangGraph, FAISS (Vector Stores), PyTorch
Machine Learning
Supervised & Unsupervised Learning (Random Forest, XGBoost, Clustering), Scikit-learn, Model Validation (PSI)
Deployment & Model Serving
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, Power BI (DAX), Tableau, Matplotlib, Vintage Analysis
Automation & Tools
UiPath, 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 😀