Data Scientist
hace 22 horas
Our team is directly involved in the development of analytical solutions, including credit risk metrics, supply risk, interest rate risk, liquidity risk, and climate risk.
Our data scientists contribute to projects in every phase, including data analysis, methodology design, model development and improvements, documentation writing, results delivery, and interpretation.
We offer:
- Outstanding development opportunities and ample training - technical and otherwise -.
We handle a wide variety of projects, so there are plenty of opportunities to work with a diverse team of experts in multiple quantitative fields.
- Access to some of the largest and richest datasets in the world.
- Exposure to a global client base, including key lenders, asset managers, insurers, corporations, and governments.
- Opportunities to see your research implemented and brought to the market on a large scale.
You may make a lasting impact on the financial system.
- Competitive compensation.
- Excellent Work-Life balance.
Required:
- Master's or Ph.D. in Financial Engineering, Data Science, Computer Science, Statistics, Economics, Econometrics, Mathematics, Physics, Finance, or any other quantitative field, or bachelor's with at least two years of work experience.
- Strong programming skills in R and/or Python.
- Excellent English communication skills.
- Ability to communicate both verbally and in writing specialized content in a clear and concise way to technical and non-technical audiences.
Preferred:
- Experience with SQL.
- Data wrangling experience.
- AWS experience: EC2, Athena, S3.
LI-MM2
LI-Hybrid
PA Cred Dflt Modlg Soltns
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.
Moody's is a global integrated risk assessment firm that empowers organizations to make better decisions.
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