Prabhnoor Kaur
Data Science student at The University of British Columbia
Driven Data Science student at The University of British Columbia, passionate about applying machine learning and analytics to transform data into impactful, real-world solutions.
About Me
I’m a Data Science student with a strong foundation in statistics, machine learning, and data analytics. I enjoy transforming complex datasets into clear insights through modeling, visualization, and dashboard design. My work spans predictive modeling (KNN classification, churn prediction), interactive data visualization (Tableau, Altair), and full-stack analytical applications built in Python, R, SQL, and Java.
I have experience working across the full data lifecycle from data cleaning, feature engineering, and exploratory analysis to model validation, performance evaluation, and insight communication. I apply structured methodologies such as cross-validation, stratified sampling, and data-driven experimentation to ensure accuracy, reliability, and business relevance.
Beyond technical skills, I value clarity, structure, and communication ,whether I’m building a model, designing a dashboard, or presenting findings to stakeholders. I’m especially interested in applying data-driven solutions to real-world problems in healthcare, business, and technology, and continuously refining my ability to bridge technical analysis with strategic decision-making.
Recent Developments
Explore my newest projects | academic research | professional achievements.
Breast Cancer Classification Model
Breast Cancer Classification Model Built a KNN classification pipeline with stratified splitting and 10-fold cross-validation, achieving 95% test accuracy with only 3 false negatives (5.7% miss rate).
FLT3 Genomic Classification
Engineered and modeled structured genomic data to predict mutation pathogenicity in a real-world bioinformatics internship setting.
Newsletter Subscription Prediction
Cleaned and standardized behavioral data, applied cross-validated KNN with upsampling, and achieved 87% precision while identifying 15–25-year-old high-engagement users as top subscribers.
Vancouver City FC – Revenue Growth Analysis
Vancouver City FC Revenue Growth Analysis Performed end-to-end ETL and trend analysis on operations and sales data to generate data-driven revenue optimization recommendations across three business streams.
Infection Mortality Patterns Dashboards
Infection Mortality Patterns Dashboard Analyzed and integrated IHME and FAO datasets to build interactive Altair dashboards uncovering relationships between mortality trends, funding, R&D, and environmental factors.
Industry Work Experience
Machine Learning Student Intern
Jan 2026 – Present
RJH Biosciences
Built structured dataset for FLT3 mutation classification by parsing 200+ genomic variants into engineered features and integrating public ClinVar data. Eliminated duplicate leakage and improved benign class representation from 7% to ~23%, strengthening dataset balance and model reliability. Currently developing machine learning models to predict mutation pathogenicity, applying rigorous preprocessing, feature engineering & performance evaluation techniques within a bioinformatics research setting.
Centre Assistant
Sept 2025 – January 2026
Kumon-Sullivan
Delivered client-facing academic support through structured communication with students and parents, ensuring clarity, professionalism, and progress tracking. Managed performance data, maintained organized student records, and prepared weekly analytical progress reports across two subjects, reinforcing data accuracy and structured documentation practices.
Research Project Specialist
Sep 2025 – Jan 2026
UBC Chemical &
Biological Engineering
Collected, validated, and managed analytical data from 10–20 soil samples monthly following structured research protocols. Maintained high data integrity standards and prepared analytical summaries to support research planning and technical reporting. Ensured accurate documentation for reproducibility and compliance.
Data Analyst Intern
Hindustan Enterprisers
Feb 2023 – Apr 2024
Performed large-scale data preprocessing and validation on structured datasets (10,000+ records) to support operational and business decisions. Developed analytical reports and insight-driven summaries using Python and Excel, translating technical findings into actionable recommendations for both technical and non-technical stakeholders.