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About

Hey there! Thank you for dropping by! My name is Jared Perez and I am a data scientist, analyst, software engineer, exercise physiologist and sport scientist. In my free time I like walking dogs, learning new technical skills, working on new engineering projects, olympic weightlifting, and jumping out of airplanes. I hope you enjoy exploring this webpage as much as I enjoyed making it and get to learn a little about me in the process.

To learn more about my journey from exercise, sport, and coaching to data and engineering. Check out the 'My Story' page.



See some more of my work

Skills

Back-End

  • Django
  • Python
  • Flask
  • Node.js
  • PostgreSQL
  • MongoDB
  • MySQL

Front-End

  • React
  • Redux
  • AngularJS
  • Next
  • JavaScript
  • TypeScript
  • Bootstrap
  • SCSS
  • CSS

Data Science

  • Python
  • R
  • Tensoflow
  • PyTorch
  • Keras
  • Tableau
  • PowerBi
  • Shiny
  • Excel

Resume

Education

Data Science & Analytics Certificate

UC-Berkeley

February 2023 - August 2023

PhD in Bioengineering - Data Science Focus (Not Completed)

Auckland University of Technology

January 2021 - January 2024 (Withdrawn)

M.S.c in Exercise Physiology

Northumbria University

April 2018 - September 2019

B.S. in Exercise Science

University of Puget Sound

August 2013 - May 2017
Experience

Research Data Scientist

John Hopkins University

Dec 2023 - Present
  • Build dynamic Tableau dashboards to represent organization data from both Airtable and Salesforce.
  • Build and maintain an ETL pipeline to clean and validate data prior to ingress into a Salesforce instance.
  • Built an NLP pipeline for analyzing qualitative responses from unstructured text data prior to storage in a Salesforce instance.
  • Built a Web Data Connector for linking AirTable to Tableau with Typescript and Taco toolkit.
  • Built a dynamic network graph GUI to track the career trajectories of Bloomberg Center program participants.

Data Science & Analytics Instructor

UC Irvine (EdX Bootcamps)

Aug 2023 - Present
  • Teach a class of 30 students advanced data topics including Excel, Python, Google Cloud, Tableau, JavaScript, HTML/CSS, PostgreSQL, Spark, Microsoft Azure, API integrations, social media mining, and machine learning.
  • Proficiently utilize Git to maintain, update, and manage assignment and project repositories on GitHub.

Data Scientist

Auckland University of Technology

Jan 2021 - Jan 2024
  • Spearheaded the development of AUT’s first ‘Human Digital Twin’ Project involving 3D human modeling, computational modeling, signal processing, anthropometric data analysis, and database management.
  • Deployed ensemble Tensorflow model providing decision support to coaches reducing 8 hours of admin time per week.
  • Built an ML pipeline from electronic health records to improve patient outcomes with degenerative diseases.
  • Developed a data pipeline aimed at optimizing concussion patient processing using SQL and Python.
  • Built CNNs for computer vision applications to improve head trauma diagnosis using Tensorflow and PyTorch.

Owner

Jared Perez Bio-Analytics for Health and Performance

Jan 2021 - Present
  • Founded my own bioanalytics company that focuses on quantiative and qualitative analytics and physiological monitoring.
  • I manage and run all elements of the business including exercise prescription, data collection, data analysis, database management, and website development.
  • Deployed ensemble model providing decision support to sport coaches reducing 8 hours of admin time per week.
  • The impetus for my company was an absence of data driven approaches to resistance training prescription as outlined in my academic publication co-authored by Dr. Adam Storey and Dr. Eric Helms.
    • paper

Exercise Physiologist

Auckland University of Technology

Jan 2021 - Oct 2021
  • Investigated the role of ovarian hormone fluctutations throughout the menstrual cycle on exercise redox biology, exercise performance, and adaptations
  • Authored 3 literature reviews focused on the role of exercise redox biology in health and disease and women's health
  • Investigated physiological profiles of endurance athletes at High Performance Sport New Zealand as part of larger Sports Performance Research In New Zealand (SPRINZ) group.
  • Profiled changes in ventilatory threshold during steady state endurance cycling before and after fatiguing sprints to optimize endurance prescriptions.
  • Coordinated research studies using various equipment including force plates, metabolic cart, and isokinetic dynamometer.
  • Managed the human health and biochemistry research lab; collected blood samples, ran micro-assays, and anthropometric measurements as part of the human health and performance research group.

Performance Coach

Google

September 2019 - January 2021
  • Health and Wellness site manager for the third largest Google (San Francisco).
  • Engineered client engagement metrics that highlighted opportunities for modified health offerings leading to increased Googler interaction with services by 12% pre-pandemic.
  • Created and executed strength and conditioning programs within a variety of spaces that includes anywhere from 1 to 20+ individuals within a given session.
  • Guiding users within the Google community from both a 1:1 or group setting to reach their own respective health and wellness goals by navigating them through a variety of services offered.
  • Developed new health initiatives within the SF campus including ‘walkathon,’ SFO run club, and inter-Google team bootcamp competitions that increased engagement with fitness offerings by 12% pre-pandemic.
  • Rapidly adjusted to a virtual working environment and developed brand new digital health and fitness offerings for Google employees that still service between 10-22% of the Google workforce despite returning to office.
  • Linked internal SQL database with Tableau dashboards to dynamically track engagement changes at site.
  • Scripted applications using Python frameworks (Pandas, Numpy) to clean and organize large data sets for data visualization platforms.

Data Analyst

Newcastle Falcons Rugby Club

April 2018 - September 2019
  • Prepared weekly health and performance dashboards using GPS, accelerometer, heart rate, and other biometric data in Excel to provide health and performance insights to coaches and other shareholders.
  • Managed internal research projects to assess influence of training prescriptions and loading parameters on specific physiological qualities of interest including reactive strength index and cardiorespiratory improvements.
  • Developed and coached athletes through a new data driven return to play strategy that reduced recurring injuries by 16%.
  • Managed team PostgreSQL instance containing thousands of physiological data parameters.

Fitness Manager

24 Hour Fitness

April 2016 - June 2018
  • Part of management team that opened Tacoma club location in 2017 with a first month’s fitness profit of 217%
  • Led a team of 12 personal trainers, providing ongoing training and regular performance evaluations for staff to ensure consistent delivery of high-quality fitness services and attainment of sales goals.
  • Highest Grossing personal trainer in the club for 8 consecutive months. Grossed over $12K for all months from November 2017 - March 2018
  • Leading coach on a team of 12 personal trainers by providing high-quality fitness services and attainment of sales goals.
Projects

Major League Soccer Tracab Tactical Data Pipeline

Technologies Used: Python, SWE, SQL, Tensorflow, ETL, MongoDB, Javascript

https://github.com/jaredap1995/MLS-TracPad
  • Built a pipeline for processing and storing MLS league standard player performance data provided by optical tracking system Tracab.
  • All MLS games are recorded using Tracab proprietary software which tracks all player movement and produces JSON or ASCII files to breakdown tactical and physical player profiles
  • The pipeline streamlines the ETL process for this data from extracting via MLS provided API keys to loading into a MOngoDB style database for every player, in every game, across an entire season.
  • Critical player statitstics like distance traveled, top speed, time spent and distance at high velocity, team possesion, and player possesion times can all be calculated and easily stored via this pipeline

Jared Perez Bio-Analytics Web Application

Technologies Used: Python, SWE, SQL, Tensorflow, Scikit Learn, Pandas, Tableau

https://github.com/jaredap1995/Data-Pipeline-and-Web-App-Exercise-Prescriptions
  • Built a web application that could be used to automate my exercise prescriptions and analysis for my small business.
  • Allowed users to track progress over time, visualize training, and utilize openAI API to create custom workouts.
  • Built out a designated ensemble model as a decision support system to reduce my prescription time.

Wearable Technologies Web Scraping and NLP Based Product Sentiment Analysis

Technologies Used: SQL, Postgres, Javascript, Python, LDA Analysis, ANCOVA, Dynamic Topic Modelling

https://github.com/jaredap1995/web-scraping-and-wearable-sentiment-analysis
  • Built a custom web scraper using Javascript to scrape thousands of Amazon product reviews from wearable technologies for product and market research using various NLP techniques.
  • The project aimed to highlight important market trends and highlight relevant features within the wearable space.
  • Insights included the greatest emphasis on battery life and health tracking features followed further down the list by features like phone functionality and product aesthetics.
  • Garmin watches were ranked the highest across almost all metrics, followed closely by Apple Watches. Budget watches like the Amazfit were generally well reviewed. Worst reviewed products were Alphabet owned including Fitbit and Pixel Watch.

Computer Vision and Dense Optical Flow in the Quantification of Velocity and Force Production

Technologies Used: PyTorch, Django, Motion Trajectories, CNN, Dense Optical Flow, Clustering, Video/Image Processing

https://github.com/jaredap1995/CV-Dense_Optical_Flow
  • Quantifying force production without the use of specialized and expensive sport software like force plates.
  • Using Dense optical flow to measure velocity via the change in pixel distance between frames
  • Developing approach to get accurate distance and velcoity meausre with respect to user size without user input (height)
  • The aim of the project is for the computer vision approach be to estimate neuromuscular fatigue and/or technical deterioration over the course of subseqeunt exercises.

Unlabeled Wearable Signal Processing and Alignment

Technologies Used: Weak Supervision, Quadratic Regression, Linear Interpolation, Unsupervised Learning, ETL

https://github.com/jaredap1995/Signal-Processing-and-Alignment#signal-processing-and-alignmen
  • Developed a labeling pipeline to assign activity labels to accelerometer signals given changes in y-crossings and differences between signal amplitude.
  • Inspired by the work of one of my PhD supervisors Dr. Brian Russell and his PhD predicting fatigue with a single sensor.
  • Can be used in conjunction with ECG and other biometric data for activity labeling in the wild with unlabelled data.
Research Experience
Explore My Research Experience