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This page contains employment and education details. For non-work projects, see the rest of the site. (Some substantial projects may be excluded due to proprietary information.)
Email: gaffney.tj@gmail.com
I worked on Omnichannel Optimization, which attempts to maximize conversions from multiple channels (online, in-app, offline).
Setup incrementality experiments for data, and ensembled existing models to drive incrementality.
2022-2025LinkWrote scripts to analyze omni-shopping backend tests. Wrote proxies to estimate incrementality.
2022-2025LinkI worked on Reddit's User Understanding team, whose main task was to features for use in models, primarily recommendations. I created specific features and established patterns for aggregating content features to users and creating user embeddings. This work focused on both batch and streaming pipelines.
Built user embeddings using Collaborative Filtering and user history. Designed pipeline to resolve cold start problem. Proved predictive value in recommendation models.
2021-2022LinkAggregates content labels to user level. Project included filtering NSFW, grouping labels, and decaying. I designed and implemented. Batch feature was built with Airflow scheduler calling BigQuery scripts. Streaming feature was built with Flink. Further built User-to-Subreddit mapping using Annoy approximate nearest neighbors.
2021-2022LinkDesigned and implemented bespoke Markov chain approach to compute average time-to-discover for subreddits. Optimized and parallelized expensive matrix computation for >99% speed up.
2021-2022LinkBuilt analytics dashboard. Helped change serving pattern to increase ad slots ~8%.
2021-2022LinkCovariates are user variables that we control for when analyzing impact of A/B tests. I identified impactful covariates and wrote script to compute these.
2021-2022LinkI worked for a team called FameBit on YouTube, which facilitates organic ads in YouTube videos. More specifically I'm in a group that deals with matching creators to brands.
For various back-end projects, I've worked with audience sentiment data to aggregate to a channel-level.
2018-2021LinkDesigned and implemented model to find best YouTube channels for a client, given URL and keywords for brand/campaign.
2018-2021LinkUtilized monte carlo simulations in a patent pending application to predict views for a pool of channels.
2018-2021LinkImplemented server for CRUD operations (and export/reverse) on a payment table.
2018-2021LinkI did some side work on a project which attempted to automatically process contracts. For my part, I scraped the FCC EDGAR database to find contracts to be used by human and machine labelers.
2018-2021LinkFor a brief period, I consulted with The Innovation Group.
Leading up to Oceans Casino's relaunch, I prepared some research on the market segments, and designed their loyalty program.
2018LinkI conducted surveys and matched to Census data to model demand. I used this in a gravity model to estimate market size of sports betting in states that were considering legalizing.
2018LinkI was a manager in a group that analyzed about $500M of marketing budget; as manager, I drove the direction/workflow. We touched many branches of marketing, including direct mail, host program, events/promotions, loyalty program, and advertising. I worked on a wide range of projects, including: Ad hocs; building reports; A/B split testing of DM campaigns; goal-setting for casino hosts; market segmentation; advertising impacts; and test-analyzing survey results.
Analyses on effectiveness of digital direct mail, Asian play trends, cross-property marketing, and others.
2016-2018LinkAggregated player data and joined with the marketing data from many sources and systems.
2016-2018LinkAdvised on statistical methodology and developed software to quickly run AB testing and reporting, resulting in an 80% reduction in process time. Reporting included visualizations for drill down decision-making. Created results repository for long-term trend analysis.
2016-2018LinkModeled expected hosted players' play. Significant improvement over existing methodology.
2016-2018LinkBuilt a Tableau dashboard to show event KPIs versus benchmarks. Spearheaded initive and achieved wide roll-out to about 60 users at 15 casinos with 1000s of uses per month, becoming most-used workbook in the company.
2016-2018LinkPerformed sentiment analysis on year-end survey results, and communicated results to the company.
2016-2018LinkConducted a live game theory experiment to help decide how to bid for gaming licenses.
2016-2018LinkMy team built the models for Auto Owners' commercial line products, including TTP, commercial auto, workers comp, and others. My work was divided about equally into three tasks: Data work, modeling, and research. Data work was SQL work to pull data for our models, and the models were large general linear models.
Used an SVM on text to predict fraud from claim notes. This allowed us to automate the work of 15 FTEs.
2014-2016LinkReversed-engineered pre-packaged GLM software, allowing us to automatically produce modeling packets. This reduced a day-long project to minutes.
2014-2016LinkResearched and advised analysts in the company on dimension reduction in auto and credit datasets. We looked into PCA, partial least squares, and lasso regressions.
2014-2016LinkBuilt a customer lifetime value model of our commerical policy data.
2014-2016LinkHelped refresh our decade-old commercial auto model, combining two previous models.
2014-2016LinkI presented research on Shapley values and family errorwise rates that influenced our modeling techniques broadly.
2014-2016LinkI thought Intro to Stats at nights one summer while I was an actuary. That semester I redesigned the term project.
I was the company's only underwriting actuary. My main job was to create and maintain software to renew group insurance policies. Additionally I worked on a number of small and ad hoc projects.
Researched to understand how new legislation impacted the way that we priced policies.
2014LinkWhile in grad school, I thought a dozen classes over six semesters. These classes included algebra, math for education majors, and calculus 2 and 3. As teacher, I taught classes; met with students; wrote and graded tests; and reported grades. In my first year, I won a reward from the department for teaching.
GPA: 3.83
GPA: 3.83
As an undergraduate, I won first place at UNR in each of: The Putnam exam, the Intermountain Mathematics competition, and the university’s Association for Computing Machinery programming competition. My team of three won the designation of meritorious winner in the international COMAP Mathematics Competition in Modeling.
2007-2011LinkI participated in a number of clubs, as well as founding UNR's math club and go club.
2007-2011Link