Assisted in the development of LLM application that leverages Internal Search, External Search, and Competitor Search data to create ranked prompts for generating optimized product titles, improving Target's online visibility, resulting in an 11% increase in search visibility for Home items and a projected $20-25M in sales for Target.com.
Engineered and optimized data pipelines for Target’s Performance Engine, migrating millions of rows of data, enabling $15.5M in incremental demand sales.
Led development Facet Relevancy and Attribute Contribution Index (ACI) data pipelines, contributing to $15M in sales growth in 2021.
Enhanced Facet Feasibility and ACI pipelines, leading to $8-9M in additional sales in 2022.
Improved the Performance Engine ML model through feature engineering (OHE), boosting accuracy and efficiency, contributing to $11.5M in profit in 2022.
Developed financial-entitlement data pipelines, providing crucial insights for Performance Engine optimization.
Created automation solutions that reduced job failures and improved pipeline efficiency by 60%, mitigating system overload issues.
Created complex queries for key e-commerce metrics (add-to-cart, CTR, facet feasibility) to enhance product visibility.
Provided key queries and data insights to Data Scientists conducting sensitivity analysis on ML models, implemented neural network, and integrated hypothesis generator model script to the Performance Engine UI.
Presented machine learning contributions with team at Target’s Demo Day 2022, increasing project visibility at the executive level.
Provided critical engineering support throughout time on team, first as one of two engineers and at times as the sole engineer, ensuring business continuity and sustained team contributions despite staffing challenges.
Software Engineer Technology Leadership Program
Target
07.2019 - 02.2020
Developed and optimized a chatbot system to enhance automation within the Intelligent Digital Robotics team.
Refactored bot logic to efficiently locate work items within Target’s tariff-processing platform, improving execution speed by 10x.
Redesigned bot architecture to seamlessly integrate with new departments and allow easy expansion for future enhancements.
Created detailed troubleshooting documentation and led knowledge transfer sessions, ensuring a smooth transition for new engineers after transition to new team
Software Engineer Intern
Thomson Reuters
06.2018 - 07.2018
Developed ETL SQL & Python scripts to optimize AI-powered recommendation systems, improving ranking algorithms
Research Assistant
Stockholm University
05.2016 - 07.2016
Applied Machine Learning (AdaBoost Decision Trees) to process terabytes of daily data from the IceCube neutrino telescope, detecting whether signals represented neutrinos or other cosmic particles.
Performed A/B testing and hyperparameter tuning to improve classification performance.
Education
Bachelors Degree -
Metropolitan State University
05.2019
Skills
Spring Boot
Kotlin/ Vanilla Kotlin
Kotest Framework
Scala
C/C
Java
MYSQL
Postgres
MongoDB
Python
Groovy
Jenkins
Relevant Projects
Coupon Machine Learning Project (in progress)
Developing tool to recommend coupons based on user’s preference, using python
Constructed automated bot that scrapes various coupon websites for coupon data via Selenium
Compiled over 500k rows of data from various coupon websites via automated bot
Currently enriching raw coupon data via feature engineering