Jing Cao

Machine Learning Engineer

2024 - Current

Data Scientist

2022 - 2024

Data Scientist

2020 - 2022

Data Scientist

2019 - 2020

- Led model development to rank leads based on location and likelihood of success with cross-functional working group - Defined, built and maintained multiple model/data ETL pipelines using Apache Airflow including: geocode and calculate scores for leads, data enrichment tracking, data exporting, and high volume data importing - Designed and evaluated product experiments including: host onboarding, photographer marketing program, camper review flow etc. using Bayesian methods - Contributed to data platform by improving pipeline efficiency to provide analysts and team leads more reliable data support

Data Scientist

2017 - 2018

- Designed and evaluated experiments to test trucking app features including: in-app referrals, optimizing notification frequency, and setting flexible shipment appointments - Led analysis on user acquisition channels and onboarding conversion to inform business decisions on carrier acquisition and marketing channels - Created and maintained ETL pipelines using DBT and Airflow to warehouse data on AWS - Built logistic regression model to predict app assisted shipment acceptance - Defined product metrics and built data visualization to monitor carrier facing product performance and user engagement - Mentored junior analysts on experimental design and SQL dashboarding

Quantitative Researcher

2016 - 2017

- Processed satellite imagery data and spatial temporal field yield data using Python - Used k-means clustering algorithm to give recommendations on filed zoning and seed selections to optimize yield - Validated, cleaned and ingested new datasets to improve yield optimization models - Partnered with engineers and product managers to productionize the field zoning research

Data Analyst

2015 - 2016

- Implemented Bayesian hierarchical model using research harvest data to recommend planting density given grower’s target yield - Reduced Bayesian sampling computation time by 30% using RStan - Acquired new field research data and ensured data quality by conducting exploratory data analysis

Graduate Student Researcher

2014 - 2015

Space-Time Modeling Group (joint with UC Irvine)

Graduate Student Teaching Assistant

2014 - 2014