Senior AML Data Quality & Quant Analytics Lead

Fairygodboss; Cincinnati (OH); On-site; USD 86,000 - 172,000; Full time

Benefits offered by this job

Medical coverage

Dental & vision

401(k) with company match

Wellness program

Paid holidays & PTO

Job summary

PNC is seeking an AML Data Quality and Quantitative Analytics and Model Development Analyst Senior to strengthen data governance across AML processes. Based in Pittsburgh, PA, Cincinnati, OH or hub locations, you will lead data quality efforts and collaborate with investigators, business leaders, and tech teams.

The role targets experienced financial crimes, risk, or compliance professionals who can connect regulatory expectations with data-driven decision making, promoting data integrity and

Qualifications

• University/college degree required with 3+ years of relevant / direct industry experience.
• Experience in financial crimes, risk, or regulatory compliance preferred.
• Strong knowledge of AML data, monitoring, investigations, and regulatory reporting.

Responsibilities

• Performs advanced quantitative analyses and model development to drive decisions.
• Develops and reviews model frameworks; communicates with model owners and teams.
• Analyzes data quality and supports validation, documenting findings.
• Measures model risk using quantitative tools and explains strengths/limitations.
• Prepares detailed documents for regulatory compliance and validation.

Skills

Analytical Thinking

Credit Risks

Data Analytics

Financial Analysis

Model Development

Operational Risks

Quantitative Models

Risk Appetite

Education

Bachelors

Job description

PNC is seeking an AML Data Quality and Quantitative Analytics and Model Development Analyst Senior to strengthen data governance across AML processes. Based in Pittsburgh, PA, Cincinnati, OH or hub locations, you will lead data quality efforts and collaborate with investigators, business leaders, and tech teams.

The role targets experienced financial crimes, risk, or compliance professionals who can connect regulatory expectations with data-driven decision making, promoting data integrity and