- Developing and supporting implementation of both internal and vendor developed models, using machine learning (ML), statistical, and other quantitative methods
- Applying appropriate quantitative techniques such as exploratory data analysis, regression analysis, supervised and unsupervised learning, feature engineering, statistical sampling, and data visualization
- Preparing model documentation; overseeing the tracking and execution of all external and internal validation findings related to vendor and internally developed models
- Collaborating cross-functionally across different business lines to access data sources, understand the data being analyzed, and identify process improvement opportunities
- Producing strategic recommendations based on data analysis
- Master's Degree Required in quantitative field ; Ph.D. preferred
- 4-6+ years of experience in data modeling/statistical analysis
- Strong programming skills and ability to utilize a variety of data/analytic software languages/tools (e.g., SQL, R, Python, etc.)
- Deep knowledge of a variety of statistical concepts and procedures, such as: generalized linear models, machine learning algorithms, experimental design, stochastic processes, Markov process modeling, response surface methodology, and statistical graphics
- Proven experience working with model risk management in the model validation process.
- Experience supporting AML & Sanctions and/or consumer banking preferred but not required.
- Strong verbal communication skills required with an ability to successfully communicate analytic results, business insights and resulting business implications to non-technical business partners
- Ability to work in a team environment and collaborate with colleagues