Quant Analytics Lead Associate

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
Leverage and anticipate considerations in implementation
Advanced Microsoft Office Suite
SQL/NoSQL
Advanced Python/R/SAS
Understanding of and ability to leverage cloud-based computing
Understanding of model use, requirements, and implementation needs
Understanding of Model Risk Management process and foundations
Testing for deterioration and model health
Scale and fundamental concepts of Machine Learning
How statistical measurements are used
Advanced data techniques for modeling frameworks
Ability to produce and identify information through statistical analysis
Effectively explain model insights to peers and analytics community
Identify preferred approach given the problem statement

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

No preferred qualifications provided.