Loss Analytics Analyst 2

Job Summary

The Loss Analytics team is responsible for the short-term and long-term forecasts of various losses including bankruptcy, deceased, settlement, aged loss, recoveries, fraud, delinquencies as well as contra-revenue items such as late fees charged off and finance charges charged off across various products such as private label cards, cobranded cards, proprietary cards, and BNPL. The analyst would play a crucial role in improving the accuracy of the loss forecasting models and will closely partner with business leaders to support ad-hoc analysis requests with leader guidance. The role's work is time sensitive, which will demand an individual to be very flexible and to multi-task. This is a role with a wide breadth of learning opportunities. Utilizes analytical skills, technical skills, and data analysis tools such as SQL/SAS, Python, and Microsoft Office (Word, Excel, Powerpoint) and Essbase.

Essential Job Functions

• Develop and enhance loss forecasting models independently, perform variance analysis, and communicate findings to management.
• This task requires a deep understanding of statistical methods and the ability to translate model outputs into strategic business decisions.
• This role involves developing into a full model owner which includes tasks such as updating, monitoring and enhancing the models. - (40%)
• Support the production of monthly short-term forecasts and quarterly long-term forecasts.
• Using monthly results and seasonal trends identify additional granular segments and/or macro-economic variables to improve the forecast accuracy and communicate to direct leader.
• Proactively manage the timelines for the various deliverables to ensure the loss forecasts are completed in a timely manner. ( - (20%)
• Develop ability to maintain and build analytics dashboards using MicroStrategy to streamline and automate various loss forecasting reports. - (20%)
• Maintain regular communication with business partners to assess the impact of new policies on credit losses and fraud expense.
• Utilize SQL and Microsoft Office tools to execute daily work.. - (20%)

Minimum Qualifications

• Bachelors Degree
• 2+ years of relevant work experience

Preferred Qualifications

• Masters Degree Finance, Accounting, Statistics, Economics, Business, or related
• 3+ years of relevant work experience.