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Moody's is a global integrated risk assessment firm that empowers organizations to make better decisions.
Department
Predictive Analytics OU (EAAS OU)
Role/Responsibilities
The Single Name Research Team within the Predictive Analytics group is primarily responsible for developing credit risk and emerging risk models for public and private companies across the globe.
This role is encouraged to work with a team of quant researchers to develop industry-leading credit risk, emerging risk, and valuation models.
- Conduct sophisticated theoretical and empirical research on measurements of credit risk and fixed-income valuation.
- Partner with clients in measuring and handling risks in their portfolios, as well as assist clients and internal marketing and client services teams on the education and implementation of risk management technology.
- Collaborate with financial researchers and data analysts on research projects.
- Provide research expertise to the firm's prototype implementation and software development activities
- Presents research findings to technical and non-technical audiences internally and externally.
**Qualifications**:
- Master's or Ph.D. in finance, economics, mathematical finance, computational finance, financial engineering, data science, industrial engineering and operations research, statistics, or a closely related field.
- Expert level proficiency with statistical analysis and/or programming languages such as R and/or Python.
- Knowledge or a strong interest to learn concepts of quantitative methods in finance.
- Experience working with Refinitiv, Bloomberg, CRSP, or other related financial databases is welcome.
- Experience with AWS, GitHub, Spark, and natural language processing is helpful.
- Excellent written, oral, and presentation communication skills.
Moody's is an equal opportunity employer.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.