Payton Jones
Staff Machine Learning Engineer
MyFitnessPal
About
Payton is a Staff Machine Learning Engineer at MyFitnessPal. He has 6+ years of ML experience across health technology, edtech, and adtech. He graduated with a Ph.D. in Experimental Psychopathology from Harvard University.
Interests
- Machine Learning
- Research
- Data Science
Education
PhD, Experimental Psychopathology, 2021
Harvard University
BS, Psychology, 2016
Brigham Young University
Projects
*
Advanced Rent vs. Buy Calculator
Interactive open-source calculator and visualizations for making the decision to rent or buy
networktools R package
Tools for psychometric networks. Bridge centrality, MDS plotting, and related functions.
networktree R package
Machine learning based partitioning for psychometric network models
What Statistic? R Shiny
An interactive tool for learning statistical testing methods in R.
Experience
Staff Machine Learning Engineer
MyFitnessPal
- Create machine learning solutions for personalization on the home page, meal scan, and voice logging features
- Engineer new AI features leveraging state-of-the-art multimodal LLMs
- Mentor team members and improve the maturity, reliability, and scalability of machine learning capabilities
Senior Data Scientist (Tech Lead)
Moloco
- As Tech Lead, analyze, manage, and improve a massive ad-tech data ecosystem including internal and third-party data with billions of records.
- Design, lead, and analyze complex experiments for ML strategies directly impacting customers with eight-figure ad spend.
- Define, develop, and engineer key metrics for operational success and ads performance.
Senior Data Scientist
Pluralsight
- Built and scaled production-level deep learning recommenders to millions of users, handling variable request volumes with <50ms latency.
- Extended personalized recommendations to 44.3% more users, boosting clickthrough rate by 25.4%.
- Pioneered the implementation of a centralized A/B testing framework, communicating experiment findings to the executive suite during product reviews.
Data Scientist
Hyka Therapeutics
- Developed machine learning recommendation algorithms for therapeutic content deliverables.
- Implemented digital phenotyping & psychometric software.
- Provided solutions for data analyses & visualizations of real-time mental health data.
Selected Publications
List of all publications (Google Scholar)
(2019).
Bridge centrality: A network approach to understanding comorbidity.
Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2019.1614898.
(2020).
Network trees: A method for recursively partitioning covariance structures.
Psychometrika, 85, 926-945. https://doi.org/10.1007/s11336-020-09731-4.
(2021).
What's in a trauma: Using machine learning to unpack what makes an event traumatic.
Journal of Affective Disorders. https://doi.org/10.1016/j.jad.2021.07.066.
(2021).
The Neurotic Treadmill: Decreasing Adversity, Increasing Vulnerability?.
Doctoral Dissertation.