Quantitative Modeling Analyst II

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Location: Tulsa
-TUL, Albuquerque
-ALBQ, Dallas
-DAL, Oklahoma City
-OKC

Areas of Interest: Risk Management

Pay Transparency Salary Range: Not Available

Final date to receive applications: 11/19/2026

BOK Financial Corporation Group includes BOKF, NA; BOK Financial Securities, Inc. and BOK Financial Private Wealth, Inc. BOKF, NA operates Trans Fund and Cavanal Hill Investment Management, Inc. BOKF, NA operates banking divisions:
Bank of Albuquerque;
Bank of Oklahoma;
Bank of Texas and BOK Financial®.

Discretionary

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.

You'll work with fraud and modeling partners to build, train, maintain and tune classification models in Data Visor. 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 Data Visor 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.

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.

• 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 Data Visor-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.

• 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…