Nimit S Sharma from 42234 Fawn Ridge Ct, Ashburn, VA 20148, age 51, Phone: 571 332-0551

Nimit Sharma Phones & Addresses

42234 Fawn Ridge Ct, Ashburn, VA 20148 • 571 332-0551
Brambleton, VA
12163 Penderview Ter, Fairfax, VA 22033 • 703 691-3516
4717 Quiet Woods Ln, Fairfax, VA 22033 • 703 803-0554
Pittsburgh, PA
20509 Morningside Ter, Sterling, VA 20165 • 703 421-9361
Vienna, VA
Atlanta, GA
Potomac Falls, VA
4717 Quiet Woods Ln, Fairfax, VA 22033 • 703 927-6154

Work

Position:

Food Preparation and Serving Related Occupations

Education

Degree:

Associate degree or higher

Resumes

Vice President, Credit Review

view source

Location:

42234 Fawn Ridge Ct, Ashburn, VA 20146

Industry:

Financial Services

Work:

Pnc Nov 1, 2014 - May 2016
Svp, Commercial Analytics and Portfolio Management
Capital One Nov 1, 2014 - May 2016
Vice President, Credit Review
Pnc Jul 2012 - Oct 2014
Svp, Risk Analytics
Freddie Mac Jun 2010 - Jul 2012
Risk Modeling Manager
Arpc Sep 2009 - Jun 2010
Director

Education:

Stanford University 2019 - 2019
Stanford University 2018 - 2018
Columbia University In the City of New York 2006 - 2009
Masters, Master of Arts, Finance Georgia Institute of Technology 1999 - 2000
Master of Business Administration, Masters, Business University of Twente 1997 - 1999
Master of Business Administration, Masters, Business Chatrapati Sahuji Maharaj Kanpur University, Kanpur 1991 - 1994
Bachelors, Bachelor of Science, Electronics Engineering, Electronics St. Xavier School - Delhi 1978 - 1991

Skills:

Credit Risk
Risk Management
Fixed Income
Data Mining
Valuation
Portfolio Management
R
Market Risk
Business Analysis
Vba
Statistics
Audit
Multifamily
Sas
Matlab
Sas/Sql
Mortgage
Mortgage Lending
Auditing
Alm
Economic Capital
Basel Iii
Risk Appetite
Ccar
Capital Management
Enterprise Risk Management
Machine Learning
Data Science

Interests:

Children
Economic Empowerment
Civil Rights and Social Action
Environment
Education
Science and Technology

Languages:

Hindi

Certifications:

Frm
Executive Data Science Specialization
Machine Learning Foundations: A Case Study Approach
Machine Learning: Regression
Garp