Summary
Overview
Work History
Education
Skills
Websites
LEADERSHIP & COMPETITION EXPERIENCE
Timeline
Generic

NICK WOLFE

Summary

Highly motivated and detailed-oriented candidate passionate about using data to improve business performance and customer experience. Skilled at leveraging data to develop actionable solutions to business challenges and utilizing data mining and data visualization to create meaningful insights. Excellent technical aptitude and knowledge of programming languages, data analytics and data visualization.


Demonstrates strong analytical, communication, and teamwork skills, with proven ability to quickly adapt to new environments. Eager to contribute to team success and further develop professional skills.

Overview

1
1
year of professional experience

Work History

Performance Analytics Intern

Syracuse University Football Team
04.2025 - Current
  • Process and analyze Catapult GPS tracking data to monitor athlete workload and recovery
  • Built dashboards and analysis tools for Athletic Training staff using R-based ShinyApps
  • Collaborate with trainers to identify performance insights and areas for future research

Education

Bachelor of Science - Sport Analytics, Minor in Finance

Syracuse University, David B. Falk College of Sport
Syracuse, NY
05.2027

Skills

  • Programming Languages: Python, R, SQL
  • Machine/Deep Learning: Decision Trees (XGBoost, Random Forest), Transformer Modeling
  • Data Analysis: Logistic & Multinomial Regression, K-means Clustering, GMM Clustering
  • Data Visualization: Tableau
  • Software & Platforms: Microsoft Office, GitHub
  • Deep learning
  • Time series analysis

LEADERSHIP & COMPETITION EXPERIENCE

President, Syracuse University Football Analytics Club

Aug 2025 - Present

  • Lead weekly meetings for 70+ members focused on NFL and college football analytics
  • Organize projects such as position group optimization using advanced efficiency metrics

2026 NFL Big Data Bowl Competition

Dec 2025

  • Helped develop a scoring system to measure receiver route-adjustment against league median, and their corresponding defender's closing ability given large-scale tracking data (~ 4.8 million rows)
  • Findings successfully identified many top receivers as our metric leaders

2025 Sports Info Solutions Football Analytics Blitz

Jan 2025

  • Led 4-person team to victory in our respective room against competing universities
  • Analyzed NFL Dynamic Kickoff rule using statistical methods, identifying 57% increase in returns and 35% injury reduction Applied logistic regression and multinomial models to establish strategic "kicking value" frameworks

Timeline

Performance Analytics Intern

Syracuse University Football Team
04.2025 - Current

Bachelor of Science - Sport Analytics, Minor in Finance

Syracuse University, David B. Falk College of Sport