Lead Data Scientist2019 - PRESENTMobilads
- Responsible for the construction and optimization of a geospatial system that maps physical ad impressions based on vehicle GPS data and mobile GPS data. The Mobilads geospatial system was successfully built to operate worldwide and built to scale to thousands of vehicles and billions of GPS points.
- Built automated reporting systems for the clients of Mobilads to demonstrate the technology.
- Continuously built up the company's IP portfolio through the integration of census, geotracking, and social data to enrich what Mobilad's knows about the people that see their vehicles. This ensures consistent industry-leading return on ad-spend.
CEO (Previously Chief Data Scientist)2017 - 2019Sigmai
Technologies: Python, Keras, TensorFlow, R
- Led a team of 15 data scientists, linguists, software engineers, product managers, and sales professionals.
- Focused primarily on deep learning for text classification with Keras and Tensorflow, and its integration within a rule-based NLP system.
- Developed an out-of-memory document clustering system to allow the clustering of billions of news articles.
- Built a natural language processing (NLP) system that rivaled the best NLP companies in finance, and led to data trials with some of the largest fund managers.
- Led and oversaw the Newsful application (app.Newsful.io) that was shortlisted for the 2018 SIIA CODiE Award. The business operations were acquired by Commetric (https://commetric.com).
Contract Data Scientist2017 - 2018Dreamtalents
Technologies: Python, Google Cloud
- Designed an end-to-end machine learning application using Google Cloud to serve as an API for the front end team.
- Matched candidates with businesses by utilizing staff demographic data, historical job data, and interview transcripts.
Data Scientist2016 - 2018Zalando
Technologies: Python, Spark, R
- Built analytical tools and ETL pipelines in Spark on AWS.
- Built predictive tools for targeting audiences for specific ad campaigns.
- Developed interactive data applications for product owners using Python and R (Shiny) to automate time-consuming analysis tasks (customer journeys, return on ad spend).
- Developed a system to optimize how ads are placed within the search and recommendation engine to reduce lost revenue due to poor ad placement by up to $0.5 million USD per month.
- Designed a system for determining the causal impact of multiple concurrent ad campaigns (off-site, on-site, banner Ads, and full-page ads) using regression and Bayesian time-series models.