Performance Science & Data Analytics Specialist

Andres Perez

San Diego, CA 980-***-**** **************@*****.*** LinkedIn Previous Work until May 2023 EDUCATION

Point Loma Nazarene University – San Diego, CA September 2025 – August 2026

• Master of Science in Kinesiology – Concentration in Biomechanics University of North Carolina at Charlotte – Charlotte, NC August 2019 – May 2023

• Bachelor of Science in Systems Engineering (BSSE) – Minor in Mathematics WORK EXPERIENCE

Performance Science Associate – Detroit Tigers – Lakeland, FL January 2024 – December 2024

• Completed over 15 projects primarily focused on biomech research in R in the development complex lab

• Queried, cleaned, and conducted analyses using Hawkeye and KinaTrax motion capture data for the Performance Science and Player Development departments for coaching applications

• Captured, tagged, and cleaned data using the Hawkeye (BSK) and KinaTrax motion capture systems from start to finish

• Designed and maintained structured SQL Server databases (SSMS) for organizing and querying multi-source performance data.

• Built ETL pipelines for importing and cleaning large-scale biomechanics datasets from Azure cloud environments, ensuring data uniformity and reproducibility across analyses.

• Developed interactive internal apps and dashboards for coaches to visualize real-time player motion metrics and lab outputs.

• Automated data validation, schema alignment, and version control processes to improve reliability of lab-collected motion data and reduce manual cleaning time by 40%.

• Collaborated with R&D and IT staff to optimize database performance, manage user access, and standardize naming conventions across the organization.

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Data Operator – Philadelphia Phillies – Clearwater, FL October 2022 – September 2023

• Worked at the spring training complex, assisting the FCL and minor league affiliates with Hawkeye, BSK, KinaTrax, Trackman, BATS, Rapsodo, Blast Motion, Trajekt, HitTrax, pitching/hitting reports, and other responsibilities

• Queried pitch level Hawkeye and Trackman data to improve the quality of the AAA and AA pitching scouting reports using a statistical algorithm

• Conducted analysis on infielder effectiveness comparing 1-pinky-in-the-slot fielders to 2-pinky-in-the-slot fielders at the request of the coaching staff

• Teacher Assistant - Philadelphia Phillies/SWAC Analytics Mentorship (2 months) o Worked with the R&D department to plan and assist 3 engineering mentees on a strike-called predictive modeling project

o Implemented and validated KNN, Random Forest, and Logistic Regression models for prediction o Visualized the results for presentation to illustrate predictive results, trends, and application PROJECTS

Comprehensive Transportation Sensing Systems Perception (Project Lead) August 2022 – May 2023

• Collected and processed raw-traffic data in python from real world traffic systems using LiDAR, radar, thermal, and stereo depth data capture systems outputting JSON, CSV, RGB, and thermal imaging

• Created a synchronized database to house the traffic data using PgAdmin4 and PostgreSQL

• Applied YOLO (AI) object detection, computer vision, and machine learning techniques to analyze and improve traffic systems by creating situation awareness, object classification, localization, and object tracking

• Optimized traffic flow using linear and dynamic programming mathematical calculations

• Used 3D point cloud LiDAR data to create a 3D mesh of the traffic environment Carolina Panthers Analytics Practicum (Project Lead) June 2021

• Worked with the Carolina Panthers Analytics Department to create an Advance Scouting report for divisional matchups versus the Tampa Bay Buccaneers using play-by-play data identifying tendencies, strengths, and weaknesses

• Implemented Logistic Regression models to determine which stats were most important to excel in for winning

• Visualized the results for presentation to the Panthers Analytics Department Charlotte FC Analytics Practicum June 2021

• Worked with the Charlotte FC Analytics Department to create a numerical rating system for all players entering the expansion draft

• Visualized the results in Tableau creating interactive graphs on offensive, defensive, finishing ability, shot selection, defensive discipline, and play time metrics where players can be identified

• Calculated Pearson correlations to gain a better understanding of whether crosses into the box or short passes into the box have the highest impact with team goal differentials ESPN Analytics Practicum June

2021

• Worked with ESPN’s projection team to create a power rating system for all Division 1 men’s baseball teams

• Weighted strength of schedule, offensive rating, pitching rating, and defensive rating

• Created multiple linear regression models in R to assess the impact of each metric on win/loss percentages

• Plotted the relationships between the 4 input variables of highest importance to win/loss percentage

• Predicted the win totals of the top 5 ranked teams in the 2019 season TECHNICAL SKILLS

• Proficient Software: Python, R, SQL databases, Gurobi, Git, Minitab, Arena Simulation, Tableau, Excel

• Coding Experience: Machine Learning, Monte Carlo Simulation, Linear Programming, Dynamic Programming, Experimental Designs (DOE), 3D point cloud analysis, Data Visualization, Report Generation, Shiny Apps, Statistical Analysis, Data Cleaning and Manipulation, Querying, Exploratory Data Analysis, Optimization

• Math: Statistics, Analysis of Variance (ANOVA), Differential Equations, Multivariate Calculus, Matrices and Linear Algebra, Linear & Dynamic Programming, Stochastic Modeling, Risk & Sensitivity Analysis, Monte Carlo, Discrete Event Simulation, Machine Learning, Decision Trees & Influence Diagrams, Exponential Smoothing, Critical Path Method, DOE, Demand Forecasting, Cash Flow Analysis & Cost Estimation ACCOLADES & CERTIFICATIONS

• Dean’s List – College of Engineering and Technology

• Advancing Bases – Major League Baseball (2x)

• Stocks, Bonds, & Investing: Oh My! – UNCC

• Rapsodo Pitching

• Rapsodo Hitting

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