Data Scientist I, MIRS (Hybrid - at least 3 days in NYC office)

Radian Group•New York, NY

3d•Hybrid

About The Position

The Data Scientist I, MIRS (Mortgage Insurance and Risk Services) primary functions will be data modeling and analysis, analytical framework development and the estimation and validation of credit models. This role requires the use of financial, statistical and econometric methods within a structural modeling framework while leveraging cloud computing solutions.

Requirements

Understanding of probability modeling.
Expert mathematical, statistical, and econometric understanding.
Strong analytical background, along with the ability and willingness to effectively make recommendations on transactions based on sound business judgment.
Practical proficiency of Python and working knowledge of SAS, R, or C++ for data analysis and modeling.
Ability to learn financial analysis of structured mortgage products.
Strong work ethic and independent problem-solving capabilities.
High level of motivation and intellectual curiosity.
Able to work in a team environment.
Ability to research and define new analytical methods.
Ability to communicate effectively and present results.
Bachelor’s degree or foreign equivalent and 1 year of experience, or Master’s degree or foreign equivalent and no work experience.
1 or more years of prior work-related experience without a master’s degree, with a master’s degree no prior work experience is required.

Responsibilities

Programming in support of model estimation, implementation, monitoring, and back testing.
Development and maintenance of cloud-based modeling frameworks.
Analysis of standard reporting and model performance.
Delinquency, default, prepayment, claim severity model estimation and design.
Model development and methodology research.
Creation of analytical presentations and communication of strategic business findings to management.
Analysis and recommendations on alternative credit structures, risk sharing arrangements, and/or non-traditional manners in which to participate and take on credit risk as appropriate and necessary.
Data manipulation of large files (Python, SAS, or R datasets) to identify trends and make recommendations and/or adjustments to credit/portfolio guidelines as necessary.
Perform other duties as assigned or apparent.