Remote Sas R Python Jobs in Dallas, TX (NOW HIRING)

Founded on a legacy of more than 120 years in banking, Bank OZK is much more than just a company. We’re nationally recognized as an industry leader in financial services. That means we combine exceptional service with innovative technologies to deliver smart solutions to our clients across the country. We’re investing in small businesses, fueling economies in local communities and changing skylines in the largest cities across America. Here, we're not simply filling roles. We're fostering even greater careers.

The foundation for a great career starts with an exceptional team and a comprehensive benefits package. We believe in providing our dedicated team members with the best resources to support their physical, mental and financial wellbeing, including generous PTO, 401(k) matching, health, dental, vision (and pet!) insurance as well as special perks and discounts. Learn more about Bank OZK benefits.

Responsible for building, documenting, and maintaining the fraud detection and prevention models used to identify, quantify, monitor, and mitigate the company's fraud risk exposure across enterprise operations. This role works within the Enterprise Model Development Team to advance the Bank's fraud detection capabilities using statistical modeling, machine learning techniques, rules-based systems, and hybrid approaches appropriate to the fraud risk landscape.

1. Provides strategic leadership for fraud analytics and modeling that influences executive management decisions related to fraud risk management, regulatory compliance, and operational resilience.
2. Develops quantitative and analytical monitoring metrics to measure and manage fraudulent activity across Bank OZK’s key channels, including digital account opening, mobile and merchant remote deposit capture (RDC), ACH and wire origination, Zelle, debit card transactions, ATM activity, and branch-based deposits.
3. Develops, enhances, and maintains fraud detection and prevention models across multiple fraud domains, including deposit fraud, digital channel fraud, payment fraud, identity fraud, account takeover, authorized push payment scams, firstparty fraud, and application fraud.
4. Guides and critically evaluates thirdparty vendors and consultants providing fraud models or decisioning tools. Ensures vendor models are appropriately documented, validated, monitored, and governed prior to and after production use.
5. Ensures all fraud models comply with SR 262 guidance and the Bank’s Model Development and Risk Management Program Standards, including conceptual soundness, data integrity, methodology documentation, model tiering, risk rating, validation readiness, change management, and governance controls.
6. Designs and executes comprehensive monitoring programs for fraud models, including performance metrics, implementation verification, threshold management, alert optimization, drift detection, breach management, escalation protocols, and periodic performance reviews.
7. Ensures fraud models meet regulatory expectations for explainability, transparency, and auditability. Develops interpretation frameworks, feature analysis, and decision logic documentation suitable for management, audit, and regulatory review.
8. Provides expert guidance to executive management, Fraud Risk Management leadership, risk committees, and the Board on fraud risk trends, model performance, loss drivers, and mitigation strategies.
9. Leads planning and execution of fraud model implementation in partnership with Technology, Data Engineering, and Fraud Operations. Ensures production accuracy, operational readiness, user understanding, and controlled deployment.
10. Serves as subjectmatter expert in discussions with regulators, independent auditors, and internal audits regarding fraud model design, governance, performance, and remediation activities. Prepares materials and responses for examinations and reviews.

1. Comprehensive knowledge of fraud risk management principles and fraud typologies, including deposit fraud, digital banking fraud, payment fraud, identity fraud, and account takeover.
2. Comprehensive knowledge of Model Risk Management concepts, validation expectations, and regulatory guidance applicable to banking models.
3. Comprehensive knowledge of analytical and modeling tools such as SAS, R, Python, SQL, and related data analysis technologies.
4. Knowledge of model performance evaluation, monitoring metrics, and explainability techniques.
5. Knowledge of banking operations, digital banking channels, payment systems, and fraud operations workflows.
6. Ability to communicate complex analytical concepts clearly to nontechnical audiences, including executives, regulators, and business partners.
7. Ability to demonstrate leadership, mentoring, and team development skills.
8. Ability to demonstrate strong problemsolving, critical thinking, and analytical skills.
9. Ability to produce highquality documentation, presentations, and governance materials.
10. Ability to demonstrate effective interpersonal skills, including working in a team environment and building cross-functional relationships.
11. Ability to travel for business purposes as needed.
12. Advanced quantitative and statistical skills, including classification modeling, anomaly detection, clustering, network analysis, machine learning techniques, and explainability methods used in fraud detection and prevention.
13. Skill in using computers and Microsoft Office, including Word, Excel, Access, PowerPoint and Outlook.

1. Master’s degree in mathematics, statistics, data science, computer science, finance, economics, or a related quantitative field required; PhD or other advanced degree preferred.
2. Two or more years of progressively responsible experience in fraud analytics, fraud modeling, financial crime analytics, or quantitative risk management within banking or financial services, required.
3. Experience with statistical modeling tools and data extraction technologies required.

Operate customary equipment and technology used in a business environment, with or without accommodation.

Note:   This description is not an exhaustive list of all job functions, duties, skills, and job standards required.  Other job functions, duties, skills, and standards may be added.  Management reserves the right to add or change the job requirements at any time.

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Bank OZK is an equal opportunity employer and gives consideration for employment to qualified applicants without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, disability status, protected veteran status, or any other characteristic protected by federal, state, and local law. Member FDIC.

1. Master’s degree in mathematics, statistics, data science, computer science, finance, economics, or a related quantitative field required; PhD or other advanced degree preferred.
2. Two or more years of progressively responsible experience in fraud analytics, fraud modeling, financial crime analytics, or quantitative risk management within banking or financial services, required.
3. Experience with statistical modeling tools and data extraction technologies required.