Conduct quantitative analysis including hypothesis testing and root-cause analysis on large data sets
Support the working group by identifying types of information needed for analysis or to inform business questions
Use statistical analysis and machine learning to develop, maintain, and anticipate considerations in implementation of models
Use critical thinking to use the right approach for each problem statement
Anticipate business needs and make continuous improvements to models and processes

Requirements

Bachelor’s degree in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling or other quantitative disciplines
At least 2 years of relevant experience; 1 year with Master’s or PhD
Understanding of data structures / transformations
Understanding of and ability to create data controls
Hypothesis testing / root-cause analysis
Proficiency in SQL/NoSQL
Advanced skills in Python/R/SAS
Knowledge of model use, requirements, and implementation needs
Understanding of Model Risk Management process and foundations

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

quantitative analysishypothesis testingroot-cause analysisstatistical analysismachine learningdata structuresdata transformationsSQLNoSQLPython

Soft Skills

critical thinkinganticipation of business needscontinuous improvement