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Ryan E Koralik

from Algonquin, IL
Age ~41
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Also known as:
Ryan Edward Koralik, Ryan Jennifer Koralik
Related to:
Todd L Koralik, 55Chad M Koralik, 52Florence G KoralikJames Ljr Gallagher, 55Dennis G Gallagher, 52Larry A Koralik, 77Joseph L Gallagher, 41Linda M Koralik, 75Joyce M Koralik, 77James L Gallager, 76Jennifer K Koralik, 39Sandra K Carey, 64
Connected to:
Alice F Koran, 62Claire C Koran, 51Stephanie L Koran, 39Susan L Koran, 67Wesley M Koran, 85Christopher Koranda, 44Paula A Koranda, 68Mitchell C Korando, 111Russell L Korando, 58Nathan Koranteng, 54

Ryan Koralik Phones & Addresses

  • Algonquin, IL
  • 936A Little Falls Ct, Elk Grove Vlg, IL 60007
  • Elk Grove Village, IL
  • Schaumburg, IL
  • Palatine, IL
  • Madison, WI
  • Fort Collins, CO
  • Fitchburg, WI
  • Algonquin, IL
  • Peoria, IL

Work

Company: Equable ascent financial, llc Aug 2010 Position: Operational project analyst

Education

School / High School: Colorado State University- Fort Collins, CO Aug 2010 Specialities: Master of Science in Statistics

Skills

SAS • R • SQL Server • C++ • statistical analyses • data analysis • financial analysis • research analysis • Mathematica • Matlab • Microsoft Office • Operations Management • project management • software development • technical services

Ranks

Certificate: Machine Learning

Industries

Information Services

Resumes

Resumes

Ryan Koralik Photo 1

Manager, Data Science

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Location:
4770 Whitehall Ct, Algonquin, IL
Industry:
Information Services
Work:
Kemper Jun 2012 - Sep 2012
Marketing Analyst
Nielsen Jun 2012 - Sep 2012
Manager, Data Science
Equable Ascent Financial Aug 2010 - May 2012
Operational Project Analyst
Colorado State University Aug 2008 - Aug 2010
Statistics Department Graduate Assistant
Epic Systems Jun 2006 - Jun 2008
Technical Services
Education:
Colorado State University 2008 - 2010
Master of Science, Masters, Statistics Bradley University 2002 - 2006
Bachelors, Bachelor of Science, Mathematics
Skills:
Statistical Modeling
Sas Programming
Statistics
Sql
R
Data Mining
Microsoft Office
Forecasting
Microsoft Sql Server
Statistical Data Analysis
Statistical Software
Statistical Sampling
Experimental Design
Statistical Inference
Machine Learning
C++
Problem Solving
Credit Cards
Certifications:
Machine Learning
Coursera
Ryan Koralik Photo 2

Ryan Koralik Palatine, IL

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Work:
Equable Ascent Financial, LLC

Aug 2010 to 2000
Operational Project Analyst
Colorado State University
Fort Collins, CO
Aug 2008 to Aug 2010
Statistics Department Graduate Assistant
Epic Systems, Inc
Verona, WI
Jun 2006 to Jun 2008
Technical Services
Education:
Colorado State University
Fort Collins, CO
Aug 2010
Master of Science in Statistics
Bradley University
Peoria, IL
May 2006
Bachelor of Science in Mathematics
Skills:
SAS, R, SQL Server, C++, statistical analyses, data analysis, financial analysis, research analysis, Mathematica, Matlab, Microsoft Office, Operations Management, project management, software development, technical services

Publications

Us Patents

Methods And Apparatus To Generate Consumer Data

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US Patent:
20190266620, Aug 29, 2019
Filed:
Feb 4, 2019
Appl. No.:
16/266963
Inventors:
- New York NY, US
Julie F. Banks - Palatine IL, US
Kyle T. Poppie - Arlington Heights IL, US
Ryan Koralik - Elk Grove Village IL, US
International Classification:
G06Q 30/02
G06Q 20/38
Abstract:
Methods and apparatus to generate consumer data are disclosed. An example method of selecting a sample of transaction data corresponding to a membership program includes defining a first type of member of the membership program; defining a second type of member of the membership program; calculating, via a processor, a target for the sample; selecting, via the processor, a first portion of the transaction data for the first type of member in accordance with the target; generating, via the processor, an updated target by recalculating the target with the first portion of the transaction data removed from consideration; and selecting, via the processor, a second portion of the transaction data for the second type of member in accordance with the updated target.

Methods, Systems, Apparatus And Articles Of Manufacture To Generate Projection Weights For A Panel

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US Patent:
20190164180, May 30, 2019
Filed:
Nov 30, 2017
Appl. No.:
15/827612
Inventors:
- New York NY, US
Ludo Daemen - Duffel, BE
Ryan Koralik - Elk Grove Village IL, US
Igor Uzilevskiy - Hoboken NJ, US
International Classification:
G06Q 30/02
G06Q 10/06
Abstract:
Methods, systems, apparatus and articles of manufacture to generate projection factors are disclosed. An apparatus to reduce panel imbalance errors includes a data analyzer to identify a retailer in a geographic region indicative of shopping bias. The data analyzer also is to identify households of interest in the geographic region having combined panel data, the combined panel data representing core panelist data and auxiliary data. The apparatus also includes a modeling engine to calculate potential spending of each household at one or more stores of the retailer. The potential spending is based on observed spending. The apparatus also includes a projection engine to reduce panel imbalance errors by calculating projection weights for the combined panel based on (a) the potential spending at the one or more stores and (b) social or demographic representation data of the combined panel.

Methods And Apparatus To Generate Consumer Data

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US Patent:
20160292698, Oct 6, 2016
Filed:
Nov 16, 2015
Appl. No.:
14/942024
Inventors:
- New York NY, US
Julie F. Banks - Palatine IL, US
Kyle T. Poppie - Arlington Heights IL, US
Ryan Koralik - Elk Grove Village IL, US
International Classification:
G06Q 30/02
Abstract:
Methods and apparatus to generate consumer data are disclosed. An example method of selecting a sample of transaction data corresponding to a membership program includes defining a first type of member of the membership program; defining a second type of member of the membership program; calculating, via a processor, a target for the sample; selecting, via the processor, a first portion of the transaction data for the first type of member in accordance with the target; generating, via the processor, an updated target by recalculating the target with the first portion of the transaction data removed from consideration; and selecting, via the processor, a second portion of the transaction data for the second type of member in accordance with the updated target.
Control profile
Ryan E Koralik from Algonquin, IL, age ~41 Get Report