Summary
Overview
Work History
Education
Skills
Websites
Selected Projects
Leadership Experience
Timeline
Generic

Kimberley Maldonado

Maywood

Summary

Data scientist with a background in fashion, healthcare, and behavioral research. I build interpretable, human-centered models that bridge technical rigor with creative insight spanning customer segmentation, medical decision-making, and recommendation systems.

Overview

1
1
year of professional experience

Work History

Post-Graduate Researcher

Stevens Institute of Technology
01.2025 - Current
  • Built a LightGBM classifier to predict dialysis modality choice (home vs. in-center) using USRDS data, focusing on clinical relevance and model explainability.
  • Engineered and validated features across multiple datasets, including hemodialysis burden, physiological indicators, and social support.
  • Evaluated model performance using AUC-ROC, precision-recall curves, and SHAP values to ensure clinical interpretability.
  • Presented findings to nephrologists and data scientists; recommended stratification strategies that integrate treatment pathways with equitable access considerations.

Data Science Consultant

The Webster
10.2024 - 03.2025
  • Company Overview: Luxury Fashion Retailer - Contract
  • Partnered with The Webster to deliver advanced analytics and machine learning solutions, improving customer segmentation, targeting, and merchandising workflows.
  • Extracted data-driven insights from over 200K transactions using K-Means clustering to define behavioral patterns across 22 customer clusters, including high-value outliers and churn-prone segments.
  • Trained Random Forest and XGBoost classifiers on RFM features using scikit-learn to predict customer behavior patterns, achieving cross-validated accuracy of 90%.
  • Identified ultra-valuable customers with 3x the average purchase frequency and up to $32K in total spend, guiding targeted retention strategies and high-touch client outreach.
  • Contributed to the development of a CNN-based tool using TensorFlow for automating image-based product tagging.
  • Luxury Fashion Retailer - Contract

Education

Master of Science - Data Science

STEVENS INSTITUTE OF TECHNOLOGY
Hoboken, NJ

Bachelor of Science - Mathematics, Concentration in Statistics

MONTCLAIR STATE UNIVERSITY
Montclair, NJ

Skills

  • Python and R programming
  • Data analysis and visualization
  • Machine learning algorithms
  • Statistical modeling techniques
  • Deep learning frameworks
  • Version control with Git
  • Notebook environments and collaboration

Websites

Selected Projects

  • TENNIS ANALYTICS, Stevens Institute of Technology, BIA 678: Big Data Technologies, 09/24-12/24, Simulated user behavior and modeled engagement outcomes in a sports content setting, applying audience segmentation and predictive techniques analogous to ad tech and audience targeting use cases., Engineered 12+ features including player profile, experience, and competitive behavior to train a Random Forest model (74% accuracy) and simulate round-by-round tournament progression., Conducted player trend benchmarking (e.g., Coco Gauff, 2019-2024), identifying engagement drop-off points and improvement opportunities., Applied modeling and statistical reasoning end-to-end to real-time decision problems, analogous to ad targeting and cohort segmentation.
  • FINANCIAL VOLATILITY FORECASTING, Stevens Institute of Technology, MA 641: Time Series Analysis I, 05/24-09/24, Examined retail sales data (FRED) and Apple stock closing prices, capturing seasonal and nonseasonal financial patterns., Analyzed market volatility trends, quantifying the impact of economic events like the 2008 financial crisis and COVID-19., Applied Box-Jenkins methodology, optimizing ARIMA-GARCH models for accurate volatility forecasting., Performed rigorous model diagnostics (QQ plots, Ljung-Box tests) to validate results, improving forecasting accuracy.
  • ITALIAN AIR QUALITY MODELING, Stevens Institute of Technology, MA 544: Numerical Linear Algebra for Big Data, 09/23-12/23, Analyzed UCI Air Quality Dataset to identify major contributors to pollution in an Italian city., Developed and compared Linear Regression, KNN, and Decision Tree models for pollution level forecasting., Applied PCA and K-Means clustering to uncover daily and hourly pollution patterns, enhancing interpretability., Evaluated the impact of human activity on air quality through time-based pollution pattern analysis.

Leadership Experience

PRESIDENT, STEM STUDENT UNION, Bergen Community College, 2016-2017, Elected leader of STEM-focused student body; organized research conferences and advocated for student project funding.

Timeline

Post-Graduate Researcher

Stevens Institute of Technology
01.2025 - Current

Data Science Consultant

The Webster
10.2024 - 03.2025

Master of Science - Data Science

STEVENS INSTITUTE OF TECHNOLOGY

Bachelor of Science - Mathematics, Concentration in Statistics

MONTCLAIR STATE UNIVERSITY
Kimberley Maldonado