About

Dean Abbott

Dean Abbott is Chief Data Scientist at Appriss Retail and President of Abbott Analytics.
He is an internationally recognized thought leader and innovator in data science and predictive analytics with more than three decades of experience applying machine learning techniques to problems in customer analytics, fraud detection, personnel selection, and much more. From 2023-2024 he was the Bodily Bicentennial Professor in Analytics at UVA Darden School of Business.

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Introduction

Dean Abbott is Chief Data Scientist at Appriss Reail and President of Abbott Analytics. From 2023-2024 he was the Bodily Bicentennial Professor in Analytics at UVA DardenSchool of Business. He is an internationally recognized thought leader and innovator in data science and predictive analytics with more than three decades of experience solving problems in customer analytics, fraud detection, risk modeling, text mining, survey analysis and is frequently included in lists of the top pioneering and influential data scientists in the world. He formerly co-founded and was Chief Data Scientist of SmarterHQ.

Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014, 2nd Edition forthcoming) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing,2013). He is a popular keynote speaker and bootcamp/workshop instructor at conferences worldwide and serves on advisory boards for the UC/Irvine Predictive Analytics and UC/San Diego Data Science Certificate programs. Mr.Abbott holds a bachelor’s degree in computational mathematics from Rensselaer Polytechnic Institute and a master’s degree in applied mathematics from the University of Virginia.

Professional Experience

March 1999 to Present
Abbott Analytics
Abbott Analytics leads organizations through the process of applying and integrating leading-edge data mining and machine learning methods to marketing, research and business endeavors. Abbott Analytics has been dedicated to improving efficiency, ROI, and regulatory compliance through machine learning.

Abbott Analytics also provides bootcamp, training, mentoring and advisory services in machine learning and data science.
May 2023 – May 2024
Bodily Bicentennial Professor of Analytics
University of Virginia, Darden School of Business
In 2022, Darden initiated the Bodily Bicentennial Professorship in Analytics to advance faculty research in the field. The position was created in honor of the contributions of Sam Bodily, the John Tyler Professor Emeritus of Business Administration to the field of decision analysis. Each year, this visiting professor will offer new insights and possibilities for collaboration with Darden faculty and students.In 2022, Darden initiated the Bodily Bicentennial Professorship in Analytics to advance faculty research in the field. The position was created in honor of the contributions of Sam Bodily, the John Tyler Professor Emeritus of Business Administration to the field of decision analysis. Each year, this visiting professor will offer new insights and possibilities for collaboration with Darden faculty and students.
2020 - 2023
 Chief Data Scientist, Wunderkind
Wunderkind and SmarterHQ merge in November 2020. Remain Chief Data Scientist.
2009 - 2020
Chief Data Scientist, SmarterHQ
Actual start date was mid-2009, but I went from part-time involvement to full-time involvement on April 1, 2014.

Co-Founded SmarterHQ, bringing analytics and machine learning to retail email marketing in a SaaS context. Designed and built process to automate building of models for 100+ clients, rebuilding models as needed, either daily, weekly, or monthly. Analytics backend instrumental in obtaining the first $7M round of venture funding and future rounds.
Served as CTO of SmarterHQ for 3 years, hiring and managing the Software Development, DevOps, and Data Science teams (more than 20). Succeeded in migrating the entire backend infrastructure from SQL Server + MongoDB to Redshift + S3 + AWS microservices
1996 – 1999
Senior Research Scientist, Elder Research
Data mining consulting; financial services portfolio optimization. During this time, co-presented with John Elder KDD-98 workshop on data mining software tools; remains largest workshop attendance in KDD history.
1994 – 1996
Senior Member Technical Staff, PAR Government Systems Corp. 
Data mining and pattern recognition in signal and image processing (ASW, radar, flourescence imaging); Development of software for commercial data mining software; Optical sensor simulation and testing.
1991 – 1994
Algorithm Designer,  Martin Marietta Corp.
Built neural networks and polynomial neural networks for postal bar code reader, optical character recognition, image identification.

Radar cross-section analysis and classification (tanks, trucks, aircraft) using neural networks, including X-band, K-band, etc. Building neural networks and polynomial neural networks for postal bar code reader, optical character recognition, image identification. Radar cross-section analysis and classification (tanks, trucks, aircraft) using neural networks, including X-band, K-band, etc.
1987-1991
Research Scientist, Barron Associates, Inc.
Development of "Optimum Path-to-Go" guidance laws for missiles and glide bombs(combining polynomial neural networks with variational calculus optimum solutions)

Development of 3DOF and 6DOF simulations for guidance and control.

Development of classification models for passive ASW using polynomial neural networks
AWARD WINNING PROFESSIONAL

Advisory Boards

University of California Irvine Data Science Certificate Program
University of California Irvine Predictive Analytics Certificate Program
University of California Irvine Data Analytics for Business Certificate Program
University of California San Diego Data Mining for Advanced Analytics Certificate Program
CompEdge™ company: Pay Transparency in Real Time
2012 KDD Conference Industrial Track Program Committee
2014 KDD Conference Industrial Track Program Committee
Consulted for top companies

Partners

Orincon (now Lockheed Martin)
Elite Analytics (no longer active)
SPSS (now IBM)
Elder Research, Inc.
The Modeling Agency (now TMA, LLC)
Seer Analytics, LLC

Clients

YMCA

Partner: Seer Analytics; Survey analysis, likelihood to renew, recommend to a friend, satisfaction

 Department of Treasury: IRS (LMSB, now LB&I)

Partner: The Modeling Agency;

Noncompliance for large corporate tax returns: S-Corps (F1120S), Partnerships (F1065), C-Corps

Center for SEAL and SWCC (Navy Special Warfare Command)

Partner: Elder Research and IBM; Predict candidates who will continue Phase I training through Hell Week; Optimize candidate selection for Chief Petty Officer review.

TN Marketing

Partner: The Modeling Agency; Ensemble modeling for upsell modeling, subscription modeling

Revenue Canada

Parter: Elite Analytics; Predict tax owed by non-filer, age and recovery potential of tax debt

Department of Defense: Air Force

Partner: Intelligent Automation Corporation; Predict LD50 toxicity likelihood for compounds based on chemical structure.

 Department of Defense: Marine Corps

Partner: Orincon; Predict likelihood of future severe failure of engines

Department of Defense: Defense Finance Accounting Service

Partner: Elder Research; Identify invoices likely to be suspicious/improper; Identify government credit card misuse

Peregrine Systems (acquired by HP)

Partner: Elder Research; “Optimal IT”; model IT support bottlenecks and optimize prioritization of tickets

USAA

Partner: The Modeling Agency; Likelihood to respond to contact; customer segmentation

MetLife
Nokia

Cross-sell and churn modeling; data scientist hiring process/test

Kaiser Permanente

Partner: The Modeling Agency; Medicare customer acquisition.

Los Angeles Times

Partner: The Modeling Agency; Predict new subscriptions, renewed subscriptions; subscription forecasting

Texas Comptroller of Public Accounts

Partner: Elite Analytics; Predict age and recovery potential of tax debt

Alaska Airlines

Partner: The Modeling Agency; On-time likelihood models

Monsanto

Partner: The Modeling Agency; Metadata analysis to determine if Ragweed is resistant to Roundup (presented at Southern Weed Society conference)

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