I’m a seasoned machine learning professional, with a proven leadership record and over 10 years experience. My expertise lie in harnessing the power of data to drive business transformation - pushing the limits of what's possible on the technical side to carve out efficiencies on the business side.
I'm currently Vice President of Data Technology at Compass Digital Labs, where I grew a data practice from the ground up (consisting of Data Science, Business Intelligence, Advanced Analytics, Data Engineering, and Machine Learning Lab functional groups). Equal parts formulation, innovation, and implementation, my teams interface with Fortune 100 clients to boost their retail food operations with data-supported and data-driven strategies. We are well on our way to achieving 9-figure top line lift from our primary data projects, supporting over $20B of business from our parent company Compass Group North America. Previously, i worked at Crescendo Technology (subsidiary of Pinnacle Sports), where I was the first Data Scientist on staff. I was tasked with developing real time breaking news algorithms, as well as real-time NBA gambling machine learning models.
My PhD and PostDoc work focused on modelling the impacts of poly unsaturated fatty acids on trophic transfer efficiencies in fresh water planktonic food webs. All this through fundamental mechanistic models, culminating in a cybernetics approach. During this time, I consulted with the governments of Canada, USA, South Africa, and China on environmental and ecological model building.
Restructured team and shifted focus to navigate the Covid-19 global pandemic. Partnership with sibling teams and other analytically-minded groups across the company is a key driver in our current data pursuits. There is no economic precident for current fiscal dynamics. Using data for driving forward, as a feedback loop, a means of automation, or simply a tool to play devil's advocate, the apptetite for data-driven decisions is at an all-time high (fall, 2020).
Shifted away from building custom one-off models/reports/analyses/pipelines, and towards self-serve products and platforms. These products continue to drive both revenue and cost-savings. During this period, spun up Research and Development initiatives, encouraging employees to step outside the confines of their well defined projects for the purposes of learning/experimenting/enhancing.
Inherited (and dismantled) Business Intelligence department, forming Data Intelligence group (Data Science + Business Intelligence). Revamped Business Intelligence practices, splitting focus between reporting and Data Engineering (ETL, pipelineing, data reliability etc.). Stood up several (successful) full-stack proofs of concept for both internal and external use, demonstrating Art of the Possible style thinking.
Built Data Science team to work on data cleansing and State of the Art algorithms to drive value and data-driven mindsets within the organization. Worked closely with Marketing, Field Services, and Operations to deliver one-off data-driven narratives using modeled data built off cleansed data.
Built State of the Art news listening algorithms for contextually relevant news, while effectively filtering out noise, false signals, and amplification. Revamped existing probabilistic real-time NBA gambling models with a machine learning approach.
Built on graduate work, expanding mathematical models with intra-individual complexity, and extensibility to be plugged into agent-based environments. During this period, I also participated in extensive consulting work, with subject matters spanning aquatic oil spills (USA), holistic ecological modelling (South Africa), pre-construction knowledge sharing (China).
Side projects are a fantastic way to learn a new technology, sharpen your existing skills, and learn a new domain. A select number of my projects are presented below.