JASONKIM.IO
jason@jasonkim.io ~/portfolio

jason@jasonkim.io~$ whoami

Jason Kim

machine learning engineer (ex data scientist, ex software engineer) in sf

building and deploying deep learning models end-to-end — from experimentation and development to production deployment and real-time inference serving millions of users

jason@jasonkim.io~$ cat experience.txt

machine learning engineerdoordash | san francisco bay area | aug 2024 - present
  • Develop and deploy deep learning models to predict delivery ETAs across multiple product verticals, improving accuracy and reliability for millions of orders daily
  • Designed and launched a multitask "mixture of experts" architecture that enhanced ETA precision and reduced customer wait times in production
  • Led model training, evaluation, deployment, and A/B testing end-to-end, achieving measurable accuracy gains while maintaining key operational metrics
  • Partnered with product and experimentation teams to validate improvements through rigorous statistical testing and real-world performance monitoring
data scientistexoduspoint capital management, lp | new york city metropolitan area | jan 2023 - jul 2024
  • Joined a $13bn AUM hedge fund as the Data Science team's first hire, specializing in ML, LLM, and statistical analysis projects
  • Built and productionized ensemble forecasting models to predict macroeconomic and market behavior; automated training and deployment pipelines using AWS SageMaker and Apache Airflow
  • Designed custom ML loss functions optimized for directional accuracy and performed extensive hyperparameter tuning to improve predictive robustness
  • Created and internally deployed a Python package for generating quantitative signals from unstructured text using LLMs and retrieval-augmented generation
  • Engineered pipelines to extract insights from daily research reports, leveraging OpenAI embeddings, AWS services, and Snowflake for data storage and analytics
senior strategy analystaccenture | new york city metropolitan area | aug 2021 - dec 2022
  • Created dataset of financial statements of all publicly listed healthcare companies and conducted exploratory analysis on stock prices, industry categorizations, and other factors for a healthcare client
  • Wrote Python scripts using Google Maps API to analyze physical addresses of clinical research projects for a pharmaceutical client
  • Modeled future revenue and costs for a prospective new product offering for a home health client
software engineer internflexengage | remote | jun 2021 - aug 2021
  • Enhanced Spring Boot search functionality, enabling customers to filter receipts by date, price, and other variables
  • Developed visual feature that enabled customers to access historical marketing promotions and associated receipts
  • Conducted bug fixes, improved repositories to align with clean coding practices, and added tests to increase coverage
  • Collaborated with product management during scrum planning and participated in daily sprints and code reviews
graduate teaching assistantuniversity of pennsylvania | greater philadelphia area | sep 2019 - may 2021
  • CIS545 (Graduate) Big Data Analytics
  • CIT594 (Graduate) Data Structures & Software Design
  • CIT592 (Graduate) Mathematical Foundations of Computer Science
  • NETS213 Crowdsourcing & Human Computation
summer strategy analystaccenture | new york city metropolitan area | jun 2020 - aug 2020
  • Developed a data science platform that analyzed financial and nonfinancial data to recommend managerial actions
  • Wrote Python scripts to scrape and clean company data and computed 171 financial and 128 nonfinancial metrics for Fortune 500 companies
  • Ran 77 million correlations and identified 200 significant links between managerial actions and company performance
  • Designed a Microsoft Power BI interface to visualize significant correlations and conduct what-if analyses
summer analystj.p. morgan | san francisco bay area | jun 2019 - aug 2019
  • Provided debt financing for M&A, recapitalizations, and strategic investments for clients in the San Francisco region
  • Modeled three capitalization scenarios with varying debt levels and covenants for an oil client's acquisition
  • Calculated credit risk exposure for a higher education client using detailed cash flow projections
  • Sourced 251 prospective clients to win first place in the firm's national summer competition
research assistantuniversity of pennsylvania | greater philadelphia | jun 2016 - jun 2018
  • May 2017 - Jun 2018: Political Science, University of Pennsylvania
  • Feb 2017 - May 2017: Public Policy, The Wharton School
  • Jun 2016 - Aug 2016: International Relations, University of Pennsylvania

jason@jasonkim.io~$ cat education.txt

university of pennsylvaniamaster's degree, computer science
the wharton schoolbachelor of science, economics (finance concentration)
  • minor: international relations

jason@jasonkim.io~$ cat contact.txt