Every business that wants to be data-driven, should be.
I'd like to make that a reality, as a fractional Chief Data Officer.
10+ years of experience helping companies make better data-driven decisions
Getting started
Start-up advisor + mentor to 10+ founders on development and implementation of data strategies to power data-driven customer understanding from pre-product through release
Prioritized 40+ initiatives in collaboration with executives of major entertainment studio, based on product payoff, timeline to delivery and data availability
Panelist: Learn Insider Secrets to Data Collection and How to Use it to Scale (October)
Implementation and Iteration of data-driven decisions
Developed positive and negative KPIs to evaluate network connectivity for online gaming start-up with TB of data (220M+ requests/day)
Identified areas of missed revenue opportunities that also reduced customer churn for fashion subscription box start-up
Built end-to-end near-real time recommendation engine for a social media start-up to improve engagement of social media posts via ExtraTrees, and productionalized as an API via AWS SageMaker, Python and Docker
Training
Taught 500+ academic and industry professionals on best practices for productionalizing Machine Learning models by teaching a core graduate course at UCLA Statistics Department (2019), speaking at SoCal PyData (2018), SoCal Python (2018) and Big Data Day LA (2017)
Trained 600+ academic and industry professionals in Python, R, and various (other) topics in data science and software development
2019
Panelist: Learn Insider Secrets to Data Collection and How to Use it to Scale (October)
Speaker: Strategic Plan you Need to get your Data Product into Production: Good, Bad, and Ugly Lessons Learned from the Field (October, September)
Mentor (Pitch + Data Strategy): Glendale Tech on Tap (August)
Speaker: Writing your First Testing Suite with pytest for your Machine Learning Model (July)
Juno's Flyby mission (2018) confirmed similarities between White Oval and the Great Red Spot on Jupiter, originally detected in 2012 by image compression algorithm developed for Ph.D. thesis