• Moody's
  • $117,960.00 -188,020.00/year*
  • West Chester, PA
  • Financial Services - Insurance
  • Full-Time
  • 912 Regimental Dr

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Role/Responsibilities Moody's Analytics Credit Analytics Division, located in West Chester, PA, is a leading independent provider of consumer credit research and consulting designed to meet the diverse needs of businesses, banks, credit unions, other lenders worldwide. You would be responsible for credit modeling, including data analysis and the development, implementation, and validation of probability of default (PD), loss given default (LGD), and exposure at default (EAD) models using state-of-the-art statistical and econometric techniques. Emphasis is on consumer credit but with some exposure to corporate and other forms of risk modeling in partnership with sister departments within Moody's Analytics. You would also be responsible for other forecasting and simulation exercises, with emphasis on stress testing under alternative scenarios and IFRS9 and CECL; contract consulting work with major financial institutions and other industry players worldwide. The successful applicant would be involved in data analysis, model development, estimation and validation, final reports and documentation writing; meeting with clients to discuss current projects; making presentations; and general client service, including serving as part of a team to meet client needs for credit modeling issues. Qualifications Required Qualifications: The ideal candidate would have a Master's degree in Statistics, Mathematics, Physics, Data Science, Economics or other closely related field. At least 2 years of industry experience in quantitative risk modeling and/or loss forecasting and/or data science is preferred. Candidates with strong analytical backgrounds and programming skills in R, Stata, SAS, Python will be preferred. Ability to communicate technical subject matter clearly and concisely to individuals from various backgrounds is a plus. Excellent presentation, writing, time management and interpersonal skills are required. Preferred Quantitative analysis and creative thinking will contribute to the success of a candidate. Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion, national origin, citizen status, marital status, physical or mental disability, military or veteran status, sexual orientation, gender identity, gender expression, genetic information, or any other characteristic protected by law. Moody's also provides reasonable accommodation to qualified individuals with disabilities in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email ...@moodys.com.. This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications. For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance. For New York City positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the New York City Fair Chance Act. For all other applicants, qualified applicants with criminal histories will be considered for employment consistent with the requirements of applicable law. Click here to view our full EEO policy statement. Click here for more information on your EEO rights under the law. Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody's Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.
Credit Analyst

Associated topics: actuarial, actuarial analyst, actuarial consultant, actuary, analyst, director actuary, investment actuary, probability, retirement actuary, risk

* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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