Hi, I'm Minh Nguyen

Data Scientist

Passionate about applying machine learning, AI, and statistical methods to solve complex problems. Currently developing geospatial analytics and predictive models at Sedgwick.

About Me

From mathematics to data science

My Journey

With a Bachelor of Mathematics (Statistics major, GPA 6.6/7) and currently pursuing a Master of Data Science at University of Queensland, I've built a strong foundation in statistical modelling, machine learning, and computational mathematics.

Currently a Data Scientist at Sedgwick, I specialise in geospatial analytics and location intelligence, working with spatial data analysis, geospatial feature engineering, and proximity-based modelling. My work combines ensemble methods with geospatial techniques to extract meaningful insights from location-based data.

What I Do

  • ▹Build predictive models using ensemble methods and deep learning
  • ▹Develop geospatial analytics and location intelligence solutions
  • ▹Design data pipelines and visualisation dashboards
  • ▹Use statistical analysis to validate and explain model outputs

Experience

My professional journey

Data Scientist

Sedgwick

Sep 2024 - Present • Brisbane, Australia

  • •Designed geospatial prediction systems using ensemble methods for regional-level forecasting
  • •Engineered automated weather-driven affected area detection achieving 95%+ recall across multiple event types
  • •Implemented spatial interpolation methods aggregating point-based observations to areal predictions
  • •Built comprehensive feature engineering pipeline integrating meteorological, demographic, and terrain data
  • •Developed real-time dashboards and reports for stakeholder decision-making
PythonSQLSnowflakePower BIAzure DevOpsHEXDataikuGitVS Code

Pricing Analyst

Auto & General Insurance

Feb 2022 - Sep 2024 • Brisbane, Australia

  • •Developed and maintained GLMs for motor insurance pricing with geospatial variables and driving behaviour metrics
  • •Performed exploratory data analysis using LightGBM and SHAP values to inform feature engineering
  • •Designed and analysed A/B tests measuring impact on conversion rates and portfolio profitability
  • •Built automated data pipelines using Python and SQL for large-scale insurance data processing
  • •Conducted rate change analysis and financial forecasting to support business planning
PythonRSQLGCPVertex AISASMapInfoGitJupyter Notebook

Skills

Technologies I specialise in

Programming Languages

Python
95%
SQL
90%
R
80%
MATLAB
80%

Machine Learning & Data Science

LightGBM / XGBoost
90%
PyTorch / TensorFlow
85%
Scikit-Learn
90%
SHAP / Model Explainability
85%

Cloud Platforms

Google Cloud Platform
80%
Vertex AI / HEX
80%
Snowflake
75%
Dataiku
80%

Development & Analytics Platforms

Power BI
90%
SSMS
85%
SSRS
80%
Git / Azure DevOps
90%

AI & NLP Tools

LlamaIndex
80%
LangChain
70%
OpenAI / Claude APIs
75%
Prompt Engineering
75%

Projects

Things I've built

Portfolio Website

Modern, responsive portfolio website built with Next.js 14, TypeScript, and Tailwind CSS. Features dark mode, smooth animations with Framer Motion, and glassmorphism UI elements.

Next.jsTypeScriptTailwind CSSFramer Motion

🚧Data Quality & Model Monitoring Tool

Assessing dataset modelability and detecting model drift. Features leakage detection, impact estimation, and LLM-powered diagnostics.

PythonLLMsData Quality

🚧More Projects

Additional data science and machine learning projects currently in development. Check back soon for updates.

PythonMachine LearningData Analytics

Let's Connect

I'm open to new opportunities and collaborations

Email

Get in touch

LinkedIn

Connect with me

GitHub

View my code