Preferred Skills :
- Design, execute, and interpret statistical analyses to drive insights and strategy
- Experience in the development of statistical and machine learning models (e.g. logistic regression, random forests, gradient boosting, neural networks)
- Experience in developing credit models and/or analytics to support credit strategy
- Experience using credit bureau data to develop credit models
- Leverage creative analytical problem solving skills while using large data sets from a broad range of sources
- Query enterprise databases using SQL to obtain relevant data for analysis
- Write computer programming code in R, SAS, Python, and Scala to perform statistical analyses and develop machine learning solutions to business problems
- Use classical and modern statistical techniques (hypothesis testing, AUC, correlation analysis, clustering analysis) to draw coherent conclusions about the business's data
- Effectively reshape data to run efficiently on advanced analytics platforms including Hadoop using Spark
- Translate classical statistical methods written in SAS, R, and Python into code that can execute using Spark
- Write summary documentation of analyses performed for both technical and non-technical audiences within the firm
- Present results to peers and higher levels of management
- Share advanced machine learning and execution knowledge with team members as new techniques are discovered to solve analytical problems
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