Matthew R Radcliffe

age ~28

from Fairfield, OH

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Matthew Radcliffe Phones & Addresses

Fairfield, OH
Bloomington, MN
Boston, MA
Nashville, TN
Rossville, GA
Cincinnati, OH

Work

Company:

Dogde data and analytics
Jun 2019 to Sep 2019
Position:

Content analyst

Education

Degree:

Master of Business Administration, Masters
School / High School:

University of Cincinnati
2015 to 2020
Specialities:

Information Systems, Cybersecurity

Skills

Microsoft Office • Microsoft Word • Powerpoint • Microsoft Excel • Leadership • Training • Research • Customer Service • Javascript • Java • Public Speaking • Teamwork • Html • Windows • Css • Time Management

Languages

English

Interests

Economic Empowerment • Politics • Education • Environment • Science and Technology

Industries

Information Technology And Services

Resumes

It Telecommunications Specialist

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Location:

4539 Dues Dr, Cincinnati, OH 45246

Industry:

Information Technology And Services

Work:

Dogde Data and Analytics Jun 2019 - Sep 2019
Content Analyst
City of Cincinnati Aug 2017 - Aug 2018
It Co-Op
Microsoft Aug 2017 - Aug 2018
Product Advisor
Majestic Athletic Sep 2016 - Jan 2018
Brand Ambassador
Bob Evans Sep 2013 - Sep 2017
Server

Education:

University of Cincinnati 2015 - 2020
Master of Business Administration, Masters, Information Systems, Cybersecurity Fairfield High School

Skills:

Microsoft Office
Microsoft Word
Powerpoint
Microsoft Excel
Leadership
Training
Research
Customer Service
Javascript
Java
Public Speaking
Teamwork
Html
Windows
Css
Time Management

Interests:

Economic Empowerment
Politics
Education
Environment
Science and Technology

Languages:

English

Us Patents

System And Method For Machine Learning Based Generation Of Media Structured Products
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US Patent:

20180336577, Nov 22, 2018
Filed:

May 7, 2018
Appl. No.:

15/972642
Inventors:

- Brighton MA, US
MATTHEW C. RADCLIFFE - Brighton MA, US
International Classification:

G06Q 30/02
G06N 99/00
Abstract:

A method, computer program product, and computer system for identifying, by a computing device, event specific data of a past media program. A size of delivery of a future media program may be predicted based upon, at least in part, the event specific data of the past media program. A financial media product may be generated based upon, at least in part, the predicted size of delivery of the future media program. An actual size of delivery may be identified. A first action may be executed if the actual size of delivery is greater than the predicted size of delivery based upon, at least in part, the financial media product. A second action may be executed if the actual size of delivery is less than the predicted size of delivery based upon, at least in part, the financial media product.