Prabhnoor Kaur

I like using data to solve problems.

Data science student curious about analytics, technology, research, and the decisions behind the numbers.

Explore Work View Resume
10 projects built
$139K+ revenue loss quantified
95.9% recall on deployed ML model
200+ compounds modeled

not just one kind of data person.

Where I like to work

01

Data & Analytics

Cleaning messy datasets, finding patterns, building dashboards, and turning analysis into useful decisions.

02

Machine Learning

Building, evaluating, and deploying predictive models, with attention to data quality, validation, and real-world use.

03

Research & Experimentation

Working with scientific data, APIs, reproducible workflows, and technical problems where the answer is not obvious yet.

04

Visualization & Communication

Making technical findings understandable through dashboards, interactive tools, clear documentation, and visual storytelling.

05

Product & Project Work

Translating problems into practical tools and coordinating work across people, timelines, stakeholders, and moving pieces.

06

Collaboration & Leadership

Communicating across technical and non-technical groups, supporting teams, and taking ownership from idea to execution.

Selected work

A few things I've built, analyzed, and investigated across research, ML, analytics, and software.

Research · Machine Learning

MP Ratio Prediction

The questionCan we predict how much of a drug passes into breast milk?

Built a machine learning pipeline to estimate milk-to-plasma drug ratios using molecular and pharmacokinetic data, with a 200+ compound dataset cross-validated across ChEMBL, PubChem, and OPERA.

200+compounds
3data sources cross-validated

The findingTraced a systematic ~30 Ų surface-area discrepancy back to water of crystallization effects in source database structures : a data quality issue relevant to cheminformatics pipelines broadly.

Python · R · RDKit · PyTorch· Docker . Miniconda . REST APIs

→ also what my Computational Research Assistant role is built around
Machine Learning

FLT3 Pathogenicity Classifier

The questionIs this genetic variant pathogenic?

95.9%recall
7%→23%minority class representation

Parsed HGVS variant notation into genomic features with regex and trained 3 models for FLT3 pathogenicity classification, shipped as a live web app for real time predictions.

Python · Regex · HGVS parsing · Clinical dataset merging

Live app ↗
Data Analytics · BI

Telecom Customer Churn Dashboard

The questionWhich customers are about to leave, and what's it costing us?

$139K+revenue lost to attrition
51%churn among first-year customers

Engineered churn-flag encoding, tenure cohorts, and CLV from a 7,000+ row telecom dataset, then built a Tableau KPI dashboard surfacing where attrition concentrated.

Python · Tableau · Feature Engineering · KPI Dashboarding

GitHub ↗
Business Analytics · Datathon

Vancouver City FC — Revenue Growth

The questionWhat happened to revenue?

Ran ETL and analysis on stadium operations, merchandise, and fanbase engagement data, then delivered stakeholder facing recommendations for growing revenue across three key areas within a single datathon.

Python · pandas · NumPy · matplotlib

GitHub ↗
NLP · Statistics · Datathon

NLP & Survival Analysis for HR Retention

The questionWho's about to quit, and what's it costing us?

15–20%projected exit reduction
$2M+savings modeled

Built a pipeline across 5 datasets, VADER sentiment on Google reviews, Kaplan-Meier retention curves, logistic regression and chi-square tests to model high-performer exit probability. BOLT Datathon Semi-Finalist.

Python · pandas · VADER (NLP) · Kaplan-Meier · Logistic Regression

GitHub ↗
Software Engineering

Financial Risk Calculator

The questionHow do you track risk without spreadsheet chaos?

An object-oriented Java application with a Swing UI for adding, filtering, deleting, saving, and loading financial reports. Backed by JSON persistence, JUnit tests, and Git version control.

Java · Swing · JSON · JUnit

GitHub ↗
View all work →

Experience

Technical work, analysis, research, coordination, and the people-facing skills that sit around them.

  1. 2026

    Computational Research Assistant

    May 2026 – Present
    UBC Faculty of Pharmaceutical Sciences
    • Queried the ChEMBL API and ran everything through a multi-step filtering and validation pipeline in R to pull molecular descriptors and plasma protein binding values — got the training dataset to over 95% completeness.
    • Building a Random Forest model to predict milk-to-plasma drug ratios, wrapped in an end-to-end R package and Shiny app so researchers can go from API query to prediction without touching my code.
    • Also building PK Teaching Visualizations : interactive R Shiny apps teaching volume of distribution and drug clearance, including an SVG-animated steady-state infusion model, deployed on shinyapps.io.

    R · Machine Learning · Cheminformatics · ChEMBL API · Shiny

  2. 2026

    Program Assistant

    May 2026 – Present
    UBC Master of Data Science Program
    • Wrote Python scripts against the Google Calendar API to build, populate, and publish an entire multi-calendar academic session schedule programmatically — turned a season of manual entry into something that just runs.
    • Coordinate program administration and event logistics, running the collaborative workflow through GitHub Issues and pull requests.

    Python · Google Calendar API · Project Coordination · GitHub · Stakeholder Coordination

  3. 2026

    Machine Learning Intern

    January 2026 – March 2026
    RJH Biosciences
    • Parsed HGVS variant notation into genomic features with regex to build a structured dataset for FLT3 pathogenicity classification, then merged clinical datasets to eliminate duplicate leakage and pushed minority class representation from 7% to ~23%.
    • Built and trained an ML pipeline across 3 models landing 95.9% recall, then shipped it as a live web app for real-time predictions.

    Python · Machine Learning · Genomics · Regex · Data Quality

  4. 2025

    Centre Assistant

    September 2025 – January 2026
    Kumon–Sullivan

    Tutoring · Communication · Performance Tracking

  5. 2025

    WorkLearn Project Specialist

    September 2025 – January 2026
    UBC Chemical and Biological Engineering

    XRF Analysis · Documentation

  6. 2024

    Salaried Notetaker

    October 2024 – June 2025
    Centre for Accessibility, UBC

    Accessibility Support · Technical Notetaking · Communication

  7. 2023

    Data Analyst Intern

    February 2023 – April 2024
    Radar International
    • Cleaned, preprocessed, and validated structured datasets of 10,000+ records.
    • Built Excel and Python dashboards translating cleaned datasets into weekly KPI summaries used to make decisions.

    Python · Excel · Data Cleaning · Dashboards · KPI Reporting

tools change. fundamentals don't.

What I work with

In [1]:programming_and_data()
Out[1]:
[
  • Python
  • R
  • SQL
  • Java
  • Pandas
  • NumPy
]
In [2]:statistics_and_ml()
Out[2]:
[
  • Scikit-learn
  • XGBoost
  • TensorFlow
  • PyTorch
  • OpenCV
  • Statistical Modeling
  • Classification
  • Regression
]
In [3]:visualization_and_bi()
Out[3]:
[
  • Tableau
  • Power BI
  • R Shiny
  • Altair
  • Matplotlib
  • ggplot2
  • Excel
]
In [4]:data_and_cloud_tools()
Out[4]:
[
  • Git
  • GitHub
  • Docker
  • PostgreSQL
  • MySQL
  • Azure
  • AWS
  • Databricks
  • CI/CD
  • REST APIs
]
In [5]:research_and_technical()
Out[5]:
[
  • RDKit
  • Cheminformatics
  • Genomics
  • Data Cleaning
  • Data Validation
  • API Integration
  • Technical Documentation
]
In [6]:collaboration_and_leadership()
Out[6]:
[
  • Stakeholder Communication
  • Cross-Team Collaboration
  • Project Coordination
  • Event Planning & Logistics
  • Research Communication
  • Leadership
  • Safe Data Practices
]

Education

University of British Columbia

Expected 2028

B.Sc., Data Science - GPA 3.95 / 4.33, Dean's List

Statistics & Mathematics

Statistical Inference · Calculus I, II & III · Matrix Algebra · Applied Linear Algebra

Computing & Data

Models of Computation · Software Construction · Data Science in R & Python · Data Visualization · Machine Learning Fundamentals

projects outside the classroom.

Certifications

Riipen Labs April 2026

Rue Productions : Growth Strategy Brief

Worked with a student team on a growth strategy for Rue Productions, a Vancouver based art-house animation studio, focused on messaging & value proposition. Ran a SWOT analysis and researched international distribution and social channels to help an award winning but under marketed studio reach new audiences.

View Certificate ↗
Riipen Labs February 2026

Jill Hewlett Inc. : Growth Strategy Brief

Collaborated with a cross functional student team to build a growth strategy report for a brain fitness education and training company, using a SWOT framework to shape recommendations across the corporate, education, and wellness sectors.

View Certificate ↗

Beyond the dataset

What I do when I'm not debugging a dataframe.

Data is one part of what I enjoy. I also like building communities, coordinating projects, communicating ideas, and making things by hand.

your calligraphy photo Calligraphy
your travel photo Travel
Coffee Addict
Co-Founder & VP Logistics UBC Punjab Students Association
Data Science Student Rep UBC Data Science Club
Corporate Relations Coordinator UBC Computer Science Student Society

Let's build something interesting.

I'm always interested in opportunities to work with data, build useful tools, and solve interesting problems.

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