Analyzing large tables within extensive data marts [10B+ rows with multiple embedded arrays]
Business Intelligence (BI), Actionable Insights, Data Visualization, Machine Learning
Customer facing/presenting, production environment debugging, & DS operations in both fast-paced and structured environments.
Data science/AI blogs → Accepted into publications such as KDnuggets
Overview
5
5
years of professional experience
Work History
Associate Director, Data Analytics
Media.Monks @ YouTube
04.2022 - Current
Predicted 8M cannibalized user interactions due to similar campaigns running at the same time which led to client implementing ML audience targeting.
Tracked 1M+ impressions to recommend limiting a specific audience's ad frequency by 1 impression.
Co-led data pipeline runtime reduction by ~1-3 hours, forecasted audience reach (Python/SQL), and analyzed marketing campaigns performance (3B+ users).
Responsible for leading client conversations, creating slide decks + presenting actionable insights to stakeholders, and aligning global teams to 1 goal.
Data Scientist
Predmatic
06.2020 - 04.2023
Worked with small [< $1M] - large [> $1B] businesses & 2 DataOps startups.
Built prototype Deep Learning model for genre classification based on 1000+ songs leading to a final implemented model of ~70% accuracy.
Research Assistant
Dr. Jeremy Hourigan / UCSC (EPS)
01.2019 - 12.2019
Developed interactive R Shiny (ggplot) dashboard UI to visualize geo-chemical data.
Education
Master of Science - Analytics - Applied Machine Intelligence
Northeastern University
09.2021
Bachelor of Arts - Economics
University of California, Santa Cruz
03.2020
Skills
SQL (AWS Redshift, Apache Superset, PostgreSQL)
Python
Tableau/Looker
R
Excel / GSuite
Jupyter Notebooks
Timeline
Associate Director, Data Analytics
Media.Monks @ YouTube
04.2022 - Current
Data Scientist
Predmatic
06.2020 - 04.2023
Research Assistant
Dr. Jeremy Hourigan / UCSC (EPS)
01.2019 - 12.2019
Master of Science - Analytics - Applied Machine Intelligence