What are the responsibilities and job description for the Fraud Strategy & Model Risk Analytics [210813] position at Aquent?
Fraud Strategy & Model Risk Analytics
Manager, Fraud Analytics & Governance
Duration: 12 months, likely extension
Pay: $65 – $67 / hourly as W2
Candidates need to work 3 days onsite each week in one of the below locations:
Dallas/Irving (TX), New Castle (DE), Jacksonville (FL), Sioux Falls (SD)
Role Summary
As a key member of the Fraud Analytics, Modeling & Intelligence organization, you will design and execute data-driven fraud strategies for North American and global portfolios. This high-impact role focuses on the full fraud lifecycle—from preventing synthetic ID and application fraud to mitigating sophisticated account takeover (ATO) schemes. You will sit at the intersection of data science and risk management, leveraging large-scale datasets to build proactive defenses that safeguard our customers and the bank’s reputation.
Key Responsibilities Include
Strategy & Execution:
Lead Fraud Strategy: Design, test, and implement automated fraud risk strategies within advanced decision engines for consumer and commercial portfolios.
Lifecycle Management: Manage the end-to-end model lifecycle, partnering with developers, vendors, and Model Risk Management (MRM) to ensure models are validated, high-performing, and compliant.
Innovation: Continuously evaluate new data sources, AI/ML capabilities, and external tools to stay ahead of evolving fraud patterns.
Analytics & Insights
Advanced Data Mining: Extract actionable insights from Big Data environments (Hadoop, Hive, Python) to identify emerging attack vectors and behavioral trends.
Reporting & Governance: Support the “Authorization Governance” process by monitoring historical performance and translating complex data into clear, executive-level documentation.
Technical Documentation: Produce rigorous technical reports that meet regulatory standards and survive deep-dive audits from supervisory authorities.
Collaboration & Leadership
Cross-Functional Partnership: Act as a critical liaison between Fraud Policy, Operations, and Technology to ensure seamless execution of business priorities.
Risk Advocacy: Foster a culture of transparency and ethical judgment, ensuring all strategic decisions align with global compliance and regulatory requirements.
Qualifications
Experience: 5 years in Fraud, Payments, or Risk Analytics. Experience in the banking or fintech sector is highly preferred.
Technical Proficiency: 3 years of hands-on experience in a Big Data environment. Advanced proficiency in Python, SQL, SAS, or Hive/Impala is required.
Analytical Rigor: Proven ability to apply mathematical and statistical techniques to solve complex, real-world business problems.
Communication: Exceptional ability to “translate” technical findings into strategic narratives for senior leadership and regulatory bodies.
Autonomy: A self-starter capable of navigating a complex global matrix organization with minimal oversight.
Education
Required: Bachelor’s Degree in a quantitative field (Statistics, Mathematics, Physics, Economics, or Computer Science).
Preferred: Master’s Degree or Ph.D. in a related field.
Manager, Fraud Analytics & Governance
Duration: 12 months, likely extension
Pay: $65 – $67 / hourly as W2
Candidates need to work 3 days onsite each week in one of the below locations:
Dallas/Irving (TX), New Castle (DE), Jacksonville (FL), Sioux Falls (SD)
Role Summary
As a key member of the Fraud Analytics, Modeling & Intelligence organization, you will design and execute data-driven fraud strategies for North American and global portfolios. This high-impact role focuses on the full fraud lifecycle—from preventing synthetic ID and application fraud to mitigating sophisticated account takeover (ATO) schemes. You will sit at the intersection of data science and risk management, leveraging large-scale datasets to build proactive defenses that safeguard our customers and the bank’s reputation.
Key Responsibilities Include
Strategy & Execution:
Lead Fraud Strategy: Design, test, and implement automated fraud risk strategies within advanced decision engines for consumer and commercial portfolios.
Lifecycle Management: Manage the end-to-end model lifecycle, partnering with developers, vendors, and Model Risk Management (MRM) to ensure models are validated, high-performing, and compliant.
Innovation: Continuously evaluate new data sources, AI/ML capabilities, and external tools to stay ahead of evolving fraud patterns.
Analytics & Insights
Advanced Data Mining: Extract actionable insights from Big Data environments (Hadoop, Hive, Python) to identify emerging attack vectors and behavioral trends.
Reporting & Governance: Support the “Authorization Governance” process by monitoring historical performance and translating complex data into clear, executive-level documentation.
Technical Documentation: Produce rigorous technical reports that meet regulatory standards and survive deep-dive audits from supervisory authorities.
Collaboration & Leadership
Cross-Functional Partnership: Act as a critical liaison between Fraud Policy, Operations, and Technology to ensure seamless execution of business priorities.
Risk Advocacy: Foster a culture of transparency and ethical judgment, ensuring all strategic decisions align with global compliance and regulatory requirements.
Qualifications
Experience: 5 years in Fraud, Payments, or Risk Analytics. Experience in the banking or fintech sector is highly preferred.
Technical Proficiency: 3 years of hands-on experience in a Big Data environment. Advanced proficiency in Python, SQL, SAS, or Hive/Impala is required.
Analytical Rigor: Proven ability to apply mathematical and statistical techniques to solve complex, real-world business problems.
Communication: Exceptional ability to “translate” technical findings into strategic narratives for senior leadership and regulatory bodies.
Autonomy: A self-starter capable of navigating a complex global matrix organization with minimal oversight.
Education
Required: Bachelor’s Degree in a quantitative field (Statistics, Mathematics, Physics, Economics, or Computer Science).
Preferred: Master’s Degree or Ph.D. in a related field.
Salary : $65 - $70