Terry Elliott

Chairman and Chief Data Scientist @Bullhorn Jobscience

San Francisco, CA, US
MOBILE NUMBERS
+14•••••••08

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WORK HISTORY

Jan 2016 — Present

Chairman and Chief Data Scientist @Bullhorn Jobscience

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Artificial Intelligence (AI) is all over the news. Typically, the term is used to describe the application of statistical tools to analyze massive amounts of data to find relationships to make better decisions. The concept of machine-augmented decision making is also associated with the term. I am currently focused on machine-augmented process improvement at Jobscience.Jobscience has invested several years in looking at these questions and evaluating the best applications for artificial intelligence in our industry. Our conclusion is that, while many of the current publications feature the applications of statistical techniques that were developed during the Depression to forecast crop yields, there is a more immediate benefit from applying machine augmentation to improve recruitment management processes.

EDUCATION

1969 — 1969

Massachusetts Institute of Technology

Management Science Program

1964 — 1965

USC Marshall School of Business

Master’s Degree, Management Sciences and Quantitative Methods

1959 — 1963

University of Southern California

Bachelor’s Degree, Statistics

SKILLS

Salesforce.comApplicant Tracking SystemsNatural Language ProcessingLead GenerationCrmVenture CapitalCustomer Relationship Management (Crm)CobolStart-UpsFortranJovialNatural Language UnderstandingAccount ManagementProfessional ServicesProduct ManagementSolution SellingRecruitingQuantitative ResearchStrategic PartnershipsData ScienceCloud ComputingEnterprise SoftwareMachine LearningManagementSaasQuantitative AnalyticsLeadershipBusiness DevelopmentSoftware as a Service (Saas)Strategy

ABOUT TERRY ELLIOTT

Studied quantitative analysis, statistics and computer science at USC and MIT. Served as a senior consultant for IBM, Xerox and AT & T at SRI International. He analyzed navigational patterns of Polaris submarines for randomness for the U.S. Navy. I am currently focused on machine-augmented process improvement at Jobscience. If we can predict where a submarine skipper will go, then we can leverage technology to find the right path for talented people with machine based learning.

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