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Team Overview:
The Predictive Analytics OU 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.
Overview responsibilities:
• Data Wrangling: collection, structuring and cleaning
• Data Analysis: Driving meaningful insight from data, presenting these results internally.
• Model Development: Helping the team with model development and validation.
• Documentation: Helping the team documenting the models.
Qualifications:
• Currently studying in Economics, Financial Engineering, Statistics, Econometrics, Data Science, Computer Science, Mathematics, Physics, Finance, or any other related quantitative field.
• Experience with Python and/or R.
• Familiarity with statistical analysis using Python or R.
• Knowledge of basic traditional machine learning techniques, such as logistic regression.
• Effective communication and collaboration skills.
• Exposure to basic finance concepts
Preferred Qualifications:
• Experience with big data analysis using Spark.
• Experience with AWS services such as EC2 and S3.
• Experience with SQL.
• Familiarity with the structure and dynamics of the mortgage markets and understanding of credit risk assessment methodologies.
