To help realize the client’s objectives, this Credit Data Analyst role will have a vital part to play. The role will be challenging, but also, be mentored by the Lead Analyst to fully support deliverables to individual business units’ Risk Data Management teams, with the aim to make all risks transparent and understood. Various responsibilities starting in Business and Finance and ending in Information Technology. Assist in the Start Up, Launch, and, Enhancements of new product development to meet loan regulatory and compliance requirements for new Internet Lending Practice. Web originated loan underwriting will be an eLoan / Web 2.0 consumer lending product. Work extensively with client’s Lead Credit Analyst, to assist in their own critical Credit ScoreCard development - From Chief Internet Officer’s desk :
"Put another way, consumer lending companies are becoming much more interested in understanding their customers’ lives and psyches, because, the theory goes, knowing what makes cardholders tick will help firms determine who is a good bet and who should be shown the door as quickly as possible. Luckily for the industry, small groups of executives at most of the large firms like ours, have spent the last decade studying our customers from almost every angle, and collection agencies have developed more sophisticated dunning techniques. We have sought to draw psychological and behavioral lessons from the enormous amounts of data the credit- lending companies collect every day. They’ve run thousands of tests and crunched the numbers on millions of accounts. "
Must be a US Citizen, or, have a Green Card
Salary : To 75K Plus - D.O.E. Relocation : Available Permanent position in the Midwest : Wichita - Ranked 2 as most "Livable Communities" for its size : http://www.wichitakansas.org. and more recently, one of ten “All American Cities” : http://www.wichitakansas.org/user/file/All_America_City.pdf
DUTIES & RESPONSIBILITIES:
- Assist Lead Analyst to develop, build and deploy various statistical models used for loan loss minimization, loss forecasting, and other targeted analysis.
- Provide direct support to the Lead Analyst in the evaluation and analysis of all consumer credit risk.
- Analyze portfolio level information to identify and monitor key risk factors and develop proposed solutions. Perform ad-hoc analysis of consumer portfolios.
- Report and analyze characteristics of the Consumer Credit lines of business in relation to policies, guidelines and processes.
- Deliver portfolio analysis and performance metrics as well as create insight into new areas of concern or benefit for the portfolio.
- Monitor and evaluate problem loan statistics. Ensure that appropriate reporting of activity is occurring consistent with company policy.
- Identify and communicate to the Lead Analyst potential policy and or operational improvements that will enhance credit quality.
- Deliver requests tasked for Credit Scoring add-ons from the Lead Analyst
- Deliver requests tasked for Test Validity of statistical results from Lead Analyst
- 2+ years experience with combined online consumer lending and sub-prime risk analysis, or other high volume data intensive environments (i.e. marketing /web analytics). Previous experience with a high online transaction volume environment is highly considered.
- 2+ years experience working with Microsoft SQL Server and SQL Reporting Services, BI Tools Suite, combined with strong analytical skills in their previous experience working with large volumes of transactional data.
- Sufficient hands-on experience in Quantitative Analytics.
- Sufficient hands-on experience in SAS, SQL / Excel. Hands-on Data Aggregator experience also preferred.
- Some understanding of consumer finance industry. Sub-prime and non-secured loans a plus.
- Demonstrated ability to interpret data from intensive, fast paced tasking requests.
- Demonstrated ability to work with significant volumes of data in various formats and databases.
- Demonstrated ability to learn and understand various applications and business intelligence/database tools.
- Knowledge of credit report attributes and non-traditional data attributes preferred.
- Knowledge in logistic regression, CHAID and decision trees strongly preferred.
- Knowledge of data mining and reporting, default modeling, and loan portfolio analytics strongly recommended
- Excellent critical thinking, analytical, verbal and written communication skills.
- Degree in Economics, Statistics Mathematics, Finance, Operations Research, Computer Science or other related areas.
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