XC@xuanrui-chen

Early-career builder starting a tech career

I am beginning my professional journey, learning core skills and preparing to contribute to projects and teams.

Work samples

Selected formative projects, learning exercises, and practice work that show my developing skills and approach to problem solving.

Chicago Divvy Bike Demand and Weather Analysis Project
Chicago Divvy Bike Demand and Weather Analysis Project
Collected, cleaned, and merged over 5 million Divvy bike-sharing trip records with NOAA historical weather data using Python (Pandas), creating a clean, structured dataset for analysis. Performed exploratory data analysis, correlation studies, and linear regression to evaluate the impact of temperature, precipitation, humidity, wind speed, and temporal factors on bike-sharing demand. Visualized key patterns with Matplotlib, revealing that higher temperatures strongly correlated with increased ridership while precipitation significantly decreased demand.
PythonPandasMatplotlib
Analyzing Fairness in Machine Learning Models for Income Prediction
Analyzing Fairness in Machine Learning Models for Income Prediction
Independently completed an end-to-end machine learning project using the Adult Income Dataset, performing data cleaning, missing-value treatment, categorical feature encoding, and feature engineering with Pandas and NumPy. Developed and evaluated multiple supervised classification models using Scikit-learn to predict whether an individual’s annual income exceeded $50,000, assessing model performance through accuracy and classification results. Analyzed model predictions across demographic groups to detect potential algorithmic bias, evaluated accuracy-fairness trade-offs, and presented findings with statistical analysis and data visualizations.
PandasNumPyScikit-learn

About me

I am beginning my professional journey, learning core skills and preparing to contribute to projects and teams.

I am Xuanrui Chen. I have little formal work experience and am at the start of my career, focused on learning and building foundational skills as I prepare for professional opportunities.

Experience

Audit Intern

Grant Thornton China · Jun 2026 - Jul 2026

Financial Analysis Intern

CITIC Securities · Jul 2025 – Aug 2025

Education

University of Illinois Urbana-Champaign

Bachelor of Science in Accountancy and Data Science · Class of 2027

Skills

Learning mindsetFoundational technical skillsProject practiceProblem solvingCollaboration readiness

Back to work

Chicago Divvy Bike Demand and Weather Analysis Project

Collected, cleaned, and merged over 5 million Divvy bike-sharing trip records with NOAA historical weather data using Python (Pandas), creating a clean, structured dataset for analysis. Performed exploratory data analysis, correlation studies, and linear regression to evaluate the impact of temperature, precipitation, humidity, wind speed, and temporal factors on bike-sharing demand. Visualized key patterns with Matplotlib, revealing that higher temperatures strongly correlated with increased ridership while precipitation significantly decreased demand.

PythonPandasMatplotlib

View all work

Back to work

Analyzing Fairness in Machine Learning Models for Income Prediction

Independently completed an end-to-end machine learning project using the Adult Income Dataset, performing data cleaning, missing-value treatment, categorical feature encoding, and feature engineering with Pandas and NumPy. Developed and evaluated multiple supervised classification models using Scikit-learn to predict whether an individual’s annual income exceeded $50,000, assessing model performance through accuracy and classification results. Analyzed model predictions across demographic groups to detect potential algorithmic bias, evaluated accuracy-fairness trade-offs, and presented findings with statistical analysis and data visualizations.

PandasNumPyScikit-learn

View all work