Quantitative Modeling Analyst II

Bonus Type

Summary

At BOK Financial, your potential is our priority. We invest in people who want to grow their skills, take ownership of meaningful work and make a real impact. As a Quantitative Modeling Analyst in Fraud Risk Management, you'll help shape the fraud-detection strategy behind new product launches, starting with wires and expanding to ACH and other transaction types. You'll go beyond analyzing data: you'll help develop, train and maintain the fraud-classification models that protect our clients and build lasting trust in the bank.

Job Description

You'll work with fraud and modeling partners to build, train, maintain and tune classification models in DataVisor. A separate team prepares the data. You'll use statistical testing to find the features that matter most, then train models, review results and adjust them to improve performance. You'll also maintain the models built through DataVisor and help build new ones in-house as fraud detection expands to more products. This role is a good fit for someone who wants to own models directly.

You'll use SQL and either Python or R to work with data, measure which features matter most and help build and monitor models. Experience building or maintaining classification models is especially important. Fraud experience is a plus but not required. A background in data science, statistics, math or another quantitative field is a strong starting point.

Team Culture

Fraud Risk Management works to serve and protect with empathy and diligence. The team is collaborative and forward-thinking, and its goal is an environment where innovation can thrive and trust lasts. You'll work closely with fraud, data and technology partners. Each group brings its own expertise, and together you'll build models that stay effective as fraud patterns change. The team values curiosity, careful problem-solving and shared accountability. You'll have room to sharpen your technical skills, learn the business behind the models and bring new ideas as the fraud modeling program grows.

How You'll Spend Your Time

• Build fraud-classification models for new product launches, starting with wires and expanding to ACH and other transaction types.
• Evaluate prepared data with statistical testing to find the features that matter most for each model.
• Train models with fraud, data and technology partners, reviewing results and performance along the way.
• Maintain both DataVisor-built and in-house models so they keep working as fraud patterns and business needs change.
• Tune model settings and features based on test results and real-world outcomes.
• Partner with other teams to understand business needs, share findings and turn data into practical fraud-detection strategies.
• Document modeling approaches, assumptions, test results and changes clearly for both business and technical audiences.

Education & Experience Requirements

• Master’s Degree in Finance, Economics, or a STEM field preferred; Bachelor’s degree in Finance, Economics, or a STEM field required; CFA, FRM, CPA designations a plus
• Minimum 1 year of quantitative analysis experience in a discipline relevant to risk management to include statistical/econometric analysis, modeling, mathematics
• Minimum 1 year of experience with analytics software (SAS, R, SPSS, Matlab) and relational databases (SQL)
• Solid understanding and knowledge of model performance measures
• Solid understanding of model development and validation methodologies & processes
• Strong project management skills
• Ability to produce high quality technical documentation
• Knowledge of regulatory requirements related to model risk management (FRB/OCC SR 11-7), Basel II/III capital requirements, and Dodd-Frank Act Stress Testing (DFAST)
• Self-motivation, discipline, task focus, and a proven record of delivering high quality results within strict deadlines.
• Intellectual curiosity; superior problem-solving abilities and attention to detail; and prompt follow-through
• Ability to aggregate and synthesize complex data
• Outstanding oral and written communication skills
• Ability to present complex issues in a clear and concise manner

Working Conditions & Physical Requirements