1. Email: carmelnadav@gmail.com carmel.nadav@wellsfargo.com
CARMEL NADAV
SUMMARY
Sharp analytical business problem solver and energetic self-starter. Strong statistical
and economic background. Hands-on knowledge in developing business solutions,
mentoring colleagues and presentations. Statistical work experience includes
complaints text analytics for regulatory, reputational and operational risk. Solid
know-how of time-series forecasting and multivariate techniques (ARIMA, Cluster,
Decision Trees) as well as non-parametric and limited dependent variables (binary,
categorical) methods. Extensive work experience with large databases and Data
Mining.
EXPERIENCE
01/15 – present MKTG DBASE DEC STRAT CONS, Enterprise Data Analytics
Collaborated with various LOBs defining populations (Students, Millennial,
Insurance and more). Developed Analysts and Sr. Managers’ statistical refreshers
course material covering exploratory data analysis, predictive modeling, data mining
and machine learning. Currently building recommender system (next best product)
using game theory and, testing State Space Kalman Filtering implementation for
risk fraud detection. Evaluated R, MATLAB. Working with Bankers without Borders
developing a curriculum and teaching Statistics with R.
08/08 – 01/15 MKTG DBASE DEC STRAT CONS, Business Modeling Group-Enterprise Data
Analytics
Researched and recommended encryption algorithms, evaluated real property
databases. Developed algorithms to clean databases keys. Built production models
predicting MTG interest rates, Income and Private student loans. Developed
complaints text analytic tools supporting LOBs. Designed EXCEL-Teradata
analytical tool addressing operational, reputational and regulatory (CFPB) risks.
Collaborated with HE on several risk mitigation initiatives related to capacity to pay.
12/05 – 07/08 VP CIS Advanced Analytics WF Home Mortgage
Implemented campaign guideline and supporting analysis plans of business unit.
Developed predictive propensity, response models and evaluated portfolio risk of
MTG segment. Developed automated ETL and Data Mining algorithms. In charge of
assessment of campaigns and campaign deep dives. Developed and supported
customer segmentation. Mentored and provided guidance to peers in areas of data
analysis and statistics. Developing automated tools using SAS and VBA EXCEL.
Communicating analytical results to top management.
09/03 – 11/05 Sr. Forecaster WF Home Mortgage
Developed automated time-series forecasting system for mid/longterm range. The
application is based on SAS macros that read user's input (data source, predicted
variable, predictors, etc.), generate all possible ARIMAX models and pick the best
forecast for 5000 time series. Developed data mining tools (decision trees, neural
network models) for short/near-term forecasting. These tools use pipeline history to
generate scoring algorithms for loans in current month pipe. Managed two Jr.
analysts and mentoring two Sr. analysts. Provided ad-hot analyticssuch as turn-time
analysis of loans in the pipeline and Call Center volume.
11/02 - Marketing Analytics
09/03 Analytics Consultant
Developed data-mining tools using SAS, Excel(VBA) for major manufactures in the
CPG industry. Developed and support a web-reporting tool and a marketing

2. simulator (Excel, VBA). Developed an automated forecasting application (4,000,000
time series). Built an interactive SAS-WEB drill-down application to analyze sales
using POS data.
03/99 - Trilogy Consulting
10/02 Statistical Programmer
On assignment with Sears Credit - 06/02 – 10/02
Worked in areas of credit risk. Developed automated model-tracking-auditprograms
using SAS, SQLPLUS (Oracle) to evaluate Sears’s credit models performance.
Designed user-friendly applications to assess quality of acquisition and collection
models.
On assignment with e-acumen - 07/01 – 05/02.
Developed econometrics time series applications to model energy price risk in the
U.S. and in the European markets. Estimation and forecasting of volatility and
forward curvesfor oil, gas, fuel and electricity commodities. Developing forecast
short, mid and long run forward, futures contracts and monthly correlation for
leading utility companies in the U.S. and Europe.
Selected Presentations
Wells Fargo Machine Learning Webcast – October 20 2016. Co-Presenter provided an
overview of different machine learning techniques.
SAS Analytics Experience - Sep 20 2016. Invited speaker: “Disruptive Foresights on
Catching Financial Crises”.
WFSUG - Wells Fargo SAS user group meetings – October 20 2015. Presentation title
“Correlations – A Biography of Dangerous Ideas”. This presentation provides a review
of correlations and highlights some potential misuses
Innovators CLUB, “Peeling the Onion for Competitive Analysis & Customer
Experience”, iWeek presentation – June 8th – 12th 2015.
WFSUG - Wells Fargo SAS user group meetings – March 17 2015. Presentation title
“WOE & WaM - Disruptive Foresights on Catching Financial Crises”. Rethinking some
risk management practices and how to think outside the box with SAS
WFSUG - Wells Fargo SAS user group meetings San Francisco – April 15 2014.
Presentation title “Voice of the Customer (VOC) – Mine Your Own Business”. This
presentation is about using simple, inexpensive tools to build a sophisticated text
mining application
MCFAM Summer Symposium Modeling Risk in Banking and Insurance – Catching the
Next Crisis, School of Mathematics U of MN – July 2013, opening session catching the
next crisis – from risk taxonomy & challenges to ERM data & applications
EDUCATION
Ph.D., Applied Economics, University of Minnesota
B.S. & M.S., Applied Economics, Hebrew University