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Data Scientist I, MIRS

Radian
New York City, United Statesfull_timeVerifiedPosted 26 Mar 2025

About the role

Position:                      Data Scientist I, MIRS

Location:                     New York, NY 

Description of work to be performed:

Perform data modeling and analysis, analytical framework development and the estimation and validation of credit models. Perform programming in support of model estimation, implementation, monitoring, and back testing. Develop and maintain cloud-based modeling frameworks. Prepare model estimation and design for delinquency, default, prepayment and claim severity. Perform analysis of standard reporting and model performance. Perform model development and methodology research. Create analytical presentations and communication of strategic business findings to management. Perform analysis and recommend alternative credit structures, risk sharing arrangements, and non-traditional manners in which to participate and take on credit risk as appropriate and necessary. Perform data manipulation of large files (R, Python, or SAS datasets) to identify trends and make recommendations and adjustments to credit or portfolio guidelines as necessary. Perform other duties as assigned or apparent.

Qualifications / Requirements:

Bachelor’s degree, or foreign degree equivalent, in Finance, Economics, Mathematics, Statistics or a related field and 1 year of related experience. The position also requires 6 months of understanding of mathematical, statistical, and probability modeling; 6 months of econometric and quantitative finance concepts; 6months of strong analytical background, along with the ability to identify trends and make recommendations based on sound business judgment; 6 months of knowledge of SAS, R, C++ or python for data analysis and modelling; 6 months of data manipulation of large files (R, Python, or SAS datasets). Telecommuting may be permitted. When not telecommuting, must report at 275 Madison Ave, Suite1501, New York, NY 10016. <10% travel required. 40 hrs/wk, 8:00am-5:00pm, M-F, $82,763.00 - $103,700.00 per year.

Radian Guaranty Inc. will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a background check and drug screen (as applicable).

In the alternative, employer will accept a master’s degree or foreign degree equivalent, in Finance, Mathematics, Statistics, or a closely related field and 6 months of experience. The position also requires 6 months of understanding of mathematical, statistical, and probability modeling; 6 months of econometric and quantitative finance concepts; 6months of strong analytical background, along with the ability to identify trends and make recommendations based on sound business judgment; 6 months of knowledge of SAS, R, C++ or python for data analysis and modelling; 6 months of data manipulation of large files (R, Python, or SAS datasets). Telecommuting may be permitted. When not telecommuting, must report at 275 Madison Ave, Suite1501, New York, NY 10016. <10% travel required. 40 hrs/wk, 8:00am-5:00pm, M-F, $82,763.00 - $103,700.00 per year.

Radian Guaranty Inc. will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a background check and drug screen (as applicable).

https://careers.radian.com/us/en

REQ - R20250046

#LI-DNI

Defining Roles for Radian's Future

Understanding the qualities and characteristics that define a Leader and an Employee is important to ​building our future-fit workforce. Radian's future is only as bright as its people. For that reason, our People Plan includes profiles to support the qualities and characteristics that each Leader as well as each Employee should embody upon hire or via development.

EEO Statement

Radian complies with all applicable federal, state, and local laws prohibiting discrimination in employment.  All qualified applicants will receive consideration for employment without regard to gender, age, race, color, religious creed, marital status, gender identity, sexual orientation, national origin, ethnicity, ancestry, citizenship, genetic information, disability, protected veteran status or any other characteristic protected by ap

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