Sr. Manager, Credit Risk
Our client, a major telecommunications company in the Chicagoland area, is looking for a Sr. Manager of Credit Risk. You will be part of the Finance department and be tasked with delivering data solutions, analytical tools, campaign execution, and business insights to the company's stakeholders. Leadership experience is key, as you will be leading a team of high performing technical/analytic resources, which guide the creation and operationalization of models and other advanced analytics. This role will provide the strategy and lead the development and execution of advanced modeling techniques for managing Credit Risk, CRM initiatives, and statistical forecasting.
Responsibilities will inclue:
- Evaluating and enhancing the modeling process
- Developing models to predict customer behavior i.e. voluntary and involuntary churn, portfolio management and performance of credit policies, fraud prevention, etc.
- Developing segmentation models
- Forecasting enterprise metrics
- Developing analytically based recommendations to improve credit risk evaluation of new and existing customers; leverage analytics to predict promotions and sales channel profitability, customer behavior risk scoring, lifetime value, survival rates as well as other standard credit risk measures / analyses.
- Provide analytical leadership for the continuous evolution of credit risk strategy.
• Masters or Ph.D. in Statistics, Economics or other quantitative field.
• 12+ years of relevant experience in multiple analytical techniques and data manipulation leveraging SAS or other similar statistical tools.
• 7+ years leading, training and coaching a technical team.
• Significant knowledge in leveraging analytical techniques in Credit Risk.
• Excellent SQL and SAS skills.
• Ability to translate analytical findings into actionable customer strategies which will have a measured impact on the business required.
• Strong communication skills.
Base salary up to $170K + bonus. Must be U.S. Citizen or Green Card holder. No relocation assistance available.
Keywords: telecommunications, SQL, SAS, statistics, credit risk, segmentation, forecasting