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nicklauskim/README.md

Nicklaus Kim

Statistician • Data Scientist • Research Analyst
M.S. in Statistics (UCLA) | B.S. in Applied Mathematics (UCLA)

Summary

I recently completed my M.S. in Statistics at UCLA and am currently searching for research-oriented statistician or data scientist/analyst opportunities, particularly in the public sector. I’m passionate about using my mathematical background and programming skills to build tools like data dashboards and web applications and production-level statistical learning models. I have experience in statistical and machine learning research in academia and a diverse set of data analysis/science skills In particular, I specialize in:

  • Reproducible data workflows in Python, R, and SQL
  • Statistical modeling, machine learning, and spatial data analysis
  • Data visualization and Interactive dashboards using Dash, Plotly, and Streamlit
  • Privacy-aware modeling and synthetic data evaluation

I recently conducted research at the UCLA Trustworthy AI Lab, developing tools to audit privacy risks in synthetic data models — especially in the context of generative models in the healthcare domain.

Core Skills

Languages:
Python · R · PostgreSQL · MySQL · HTML/CSS · LaTeX

Libraries & Frameworks:
pandas · NumPy · scikit-learn · PyTorch · XGBoost · tidyverse

Dashboards & Visualization:
Dash · Streamlit · Plotly · Matplotlib · ggplot2 · Excel

Tools & Technologies:
FastAPI · Flask · AWS · Git · Jupyter

Featured Projects

NBA Play-by-Play Dashboard

An interactive basketball analytics platform with video playback
A full-stack web app for visualizing NBA play-by-play data using Dash and FastAPI.

  • Heatmaps, pass networks, scoring timelines
  • Filter by player, game, or play type
  • Dynamically loads relevant video clips
    Tech stack: Python, Plotly, Dash, FastAPI, MoviePy, SQLite

Founding Stats Dashboard

Visualizing correspondence networks and document metadata from the Founding Era
An interactive Dash app that aggregates and analyzes metadata from letters written by and to key American founders.

  • Interactive graphs showing communication frequency, relationships, and geographic trends
  • Historical document metadata enrichment and network analysis
  • Spatial and temporal visualizations of early U.S. political discourse
    Tech stack: Python, Dash, Plotly, NetworkX, spaCy, pandas

Privacy Auditing for Synthetic EHR Data

Evaluating privacy risks in synthetic health records
A research pipeline assessing de-identification and attack resilience in generative health data.

  • Membership inference simulations
  • Differential privacy scoring
  • Visualizations of trade-offs between utility and privacy
    Tech stack: Python, NumPy, pandas, scikit-learn, PyTorch

Explore More

Thanks for stopping by! Feel free to explore my pinned projects or reach out if you’re interested in collaborating or hiring.

Pinned Loading

  1. nicklauskim.github.io nicklauskim.github.io Public

    My professional website, displaying my projects and other work in statistics and data science.

    HTML 1

  2. tabular-synthetic-data-privacy-auditing tabular-synthetic-data-privacy-auditing Public

    Evaluating the privacy of tabular synthetic data generators using an adversarial toolbox, specifically the TAPAS toolbox as introduced in https://arxiv.org/abs/2211.06550. This code is used to prod…

    Jupyter Notebook 2 1

  3. nba-dash nba-dash Public

    An interactive application, built in Python using Dash, Plotly, and FastAPI, for exploring and visualizing NBA play-by-play data and video

    Python 1

  4. hyperparameter-selection-experimental-design hyperparameter-selection-experimental-design Public

    Hyperparameter Tuning for Gradient Boosting Frameworks

    R

  5. bayesian-mortality-prediction bayesian-mortality-prediction Public

    Bayesian Mortality Prediction with Sensitivity Analysis

    R

  6. machine-learning-methods machine-learning-methods Public

    Various implementations of some common machine learning algorithms in Python, including models from scratch and applied problems such as NLP tasks.

    Jupyter Notebook