Pablo López Landeros

Data Scientist and former athlete with 5+ years of experience in sports quantitative analysis, dedicated to delivering actionable insights that drive strategic decisions.

Skilled in synthesizing complex data and leveraging statistical methods to enhance organizational outcomes. Passionate about the intersection of Computing and Mathematics for descriptive and predictive modeling with applications in sports, physics, and biology.

📚 Education

B.S. Applied Mathematics

Instituto Tecnologico Autonomo de Mexico

2016 – 2020
- GPA: 8.8/10
- Graduated with honorable mention.
- Thesis: Application of Regularized Regression Methods to Forecast the NBA Playoffs.

Ph.D. Sports Analytics

University of Saarland

2024 - Present (In progress, proposal stage)
- Thesis: Modeling Penalty Kicks as a Sequential Decision-Making Process.

Certificate in Physical Data Analysis with R for Sport Scientists

Barça Innovation Hub | 2024

🔧Technical Skills

  • Foreign Language: C2 English Proficiency Certificate from Cambridge University.
  • Programming Languages: SQL (servers, dbt, BigQuery, Snowflake), Python (Pandas, Scikit-learn, StatsModels, Keras), R (dplyr, ggplot, XGBoost, Tidymodels, glmnet, STAN), MATLAB, C#, C++.
  • Machine Learning: Implementation of supervised and unsupervised models, including GLMs, neural networks, regression trees, K-means clustering, and time series forecasting.
  • Cloud Services: Google Cloud Platform (BigQuery, Kubernetes Engine, Buckets, APIs, DAGs).
  • Dashboard Creation: Microsoft Power BI, ggplotly.
  • Communication: Effective verbal and written communication skills for conveying data-driven analysis and results.
  • Reporting & Automation: Quarto, LaTeX, and Markdown.
  • Web Development: Proficient in ASP.NET (C#), Shiny (R), and basic Vue (JavaScript, CSS, HTML5).

🧪Professional Experience

Basketball Data Scientist

Zelus Analytics

November 2024 - Present
- CONFIDENTIAL BUT U CAN ASK :D

Hockey Data Scientist

Zelus Analytics

November 2022 - November 2024
- CONFIDENTIAL BUT U CAN ASK :D

Machine Learning Engineer

Engen Capital

March 2022 - November 2022
- Developed and deployed AI-driven computer vision systems to automate and expedite credit application processes, reducing response times from two weeks to three days.
- Enhanced risk assessment models by optimizing machine learning algorithms that predict applicant default probabilities.

Internship (Scouting)

Toluca F.C.

June 2021 - December 2021
- Aided with the pinpointing of potential acquisitions from minor South American leagues by leveraging advanced soccer analytics, streamlining the scouting process for coaches and scouts.

Data Scientist

Coca Cola FEMSA

January 2021 - March 2022
- Utilized multivariate time series and machine learning algorithms to refine sales forecasts, achieving a model accuracy of 90%.
- Increased zone-based sales forecasting speed by 40% using xGBoost multivariate time series and supervised regression trees algorithms.
- Evaluated the effects of Coca Cola’s marketing strategies on sales and revenue using statistical models.
- Oversaw and optimized SQL databases to improve data architecture and quality across Mexico, ensuring robust data management and enhancing overall data integrity.
- Automated internal reporting processes, reducing required labor by over 12 hours weekly.

Cybersecurity Intern

KPMG International

June 2019 - February 2020
- Implemented and managed a Power BI dashboard for data storage, EDA, and monthly reports regarding information security risks and breaches.
- Increased productivity by building pipelines to automate data processing and dashboard creation using Python and Excel.

📢 Public Projects

🎤Founder of ITAM Sports Analytics Conference

The ITAM Sports Analytics Conference aspires to be the most important sports analytics conference in Latin America.

Our mission is to drive innovation and foster collaboration within sports analytics, creating a dynamic community of experts, students, and industry leaders to share ideas, explore advancements, and shape the future of sports in Latin America.

🦠Covid 19 case estimation

Contributed to the covidmx R package, using a Bayesian model to estimate COVID-19 cases in Mexico. This was utilized by the Mexican Health Department (INSP) for safety measures.

⚽️Soccer Simulation using Monte Carlo

Developed a tool using Poisson distribution and Monte Carlo simulation to predict soccer results.

⚽️Penalty Shootout Analysis

Developed mixed-effects models to analyze penalty kicks in World Cup shootouts. Link to VOX video

🏀 NBA Playoffs Forecast & Trade Evaluation

Enhanced plus-minus metrics in my undergrad thesis, predicting the 2015 NBA playoffs and evaluating the economic impact of player trades. Link to document

🏒Win Probability Models for WNHL

Applied Expected Threat (xT) metrics for hockey to assess game outcomes in the Women’s National Hockey League (WNHL) Link to paper

E🏈ntertainment Analuysis in the NFL

Analyzed play-by-play data to gauge the evolution of perceived fan entertainment in football over two decades.

Teaching & Public Engagements🧑‍🏫

  • ITAM Sports Analytics Conference: Organizer and Founder of Latin America’s first sports tech summit on advancements in sports technology and data science.
  • Introduction to R for Health Workers: TA for a course at the National Institute of Public Health (INSP), teaching R programming and data visualization using Quarto.
  • Where to Aim a Penalty Kick: Joined Vox’s Phil Edwards for a discussion on penalty shootout analysis, examining psychological stress, dominant foot, and shooting first advantages.
  • The Role of the Sports Data Scientist: Delivered a talk at CETYS Tijuana, highlighting key responsibilities, methodologies, and the impact of data-driven decision-making in sports.

Contact Information ℹ️