Conduct quantitative analysis including hypothesis testing and root-cause analysis on large data sets with more autonomy
Support the working group by identifying types of information needed for analysis or to inform business questions create data structures/transformations to be leveraged by groups for analysis
Use statistical analysis and machine learning to develop, maintain, and anticipate considerations in implementation of models that address the right business need
Use critical thinking to use the right approach for each problem statement
Anticipate business need and make continuous improvements to models and processes

Requirements

Bachelor’s degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 2 years of relevant experience; 1 with Master’s or PhD
Understanding of and ability to:
Create data structures / transformations
Identify and capture different types of information for business needs or necessary for analysis
Data controls
Hypothesis testing / root-cause analysis
Advanced Microsoft Office Suite
SQL/NoSQL
Advanced Python/R/SAS
Cloud-based computing
Distributed computing
Model Risk Management process and foundations

Benefits

eligibility for incentive compensation which may include production, commission, and/or discretionary incentives

Applicant Tracking System Keywords

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

Hard Skills & Tools

hypothesis testingroot-cause analysisstatistical analysismachine learningdata structuresdata transformationsSQLNoSQLPythonR

Soft Skills

critical thinkingautonomycontinuous improvement