Job Description

Citibank, N.A. seeks a/ Model/Analysis/Validation Officer for its Tampa, Florida location.

Duties: Apply quantitative and qualitative data analysis methods to extract, transform and analyze AML/KYC data using SAS, R programming, Python, and SQL. Perform validation of the bank’s KYC customer risk scoring tools and Anti-Money Laundering (AML) transaction monitoring tools to ensure regulatory compliance and establish risk and controls across multiple regions and lines of business, including Retail, Institutional, Credit Cards, Markets and Private Banking. Develop, enhance and validate quantitative methodologies for measuring and analyzing financial crimes risk – AML/KYC, ensuring the rule-based and machine learning (supervised and unsupervised) techniques are robust and effective. Serve the bank’s lines of defense by providing effective challenge to AML/KYC monitoring tools throughout their lifecycle, ensuring that conceptual soundness, technical specifications, data quality, and performance are validated in accordance with regulatory requirements. Evaluate theoretical construction and implementation of tools, challenging mathematical formulation, variables selection, threshold setting and code using statistical tests, ensuring assumptions and limitations are documented to assess fit-for-purpose. Data preparation and validation for modeling and analysis, handling of missing values and outliers, variable transformations, and feature pre-selection for tool stability. Automate data extraction and data preprocessing tasks, perform ad hoc data analyses, design and maintain complex data manipulation processes using Python. Establish robust controls around data quality, continuous monitoring of data quality flowing into AML tools; checks for completeness, anomalies, drifts, and integrity within core banking and data systems Mantas and EAP/Hadoop. Execute threshold analysis to evaluate and optimize production thresholds for AML monitoring scenarios, exploring data distributions and coverage analysis using SAS, R, Python or SQL to emulate and simulate tool logic. Conduct periodic reviews of the customer segmentation tool; validate AML monitoring tool’s risk tolerance by executing testing strategies, including risk-based sampling, sensitivity analysis, and random client analysis. Review performance monitoring of AML monitoring systems, establishing risk assessment and controls through KPIs and advanced statistical metrics to validate tool. Conduct data analysis, data mining – statistical and non-statistical data exploration, read and create statistical documentation, analyze and interpret data reports and work with risk management and technology teams to address data issues and improvements to AML tools and threshold settings. Communicate analytical findings, limitations, potential risks through presentations and reports (validation report, quarterly and annual review reports) to stakeholders, management and internal governance committees, and used to inform business decisions and ensure mitigating controls are in place; provide evidence-based responses to RFIs during regulatory examinations and internal audit reviews. Lead discussions on methodology and process improvement initiatives through adoption of automation and efficiency enhancements for automation of data inputs and tool performance validation. Maintain industry leading knowledge in global banking systems and operations, including financial products, client portfolios, market exposures, evolving regulatory requirements, risk and controls, and activities such as Correspondent Banking, Payment Intermediaries and cross-border transactions applicable for AML Detection and monitoring operations. A telecommuting/hybrid work schedule may be permitted within a commutable distance from the worksite, in accordance with Citi policies and protocols.

Requirements: Requires a Master’s degree or foreign equivalent in Engineering (any), Data Science, Business Analytics, Mathematics, or related quantitative field, and 1 year of experience as a Data Analyst, Business Analyst, Banking Analyst, Officer, or related position involving AML and KYC risk and control procedures for banking services. Alternatively, will accept a Bachelor’s degree in the stated fields and 3 years of the specified experience. Full term of experience must include: Fraud detection for money laundering/terrorist financing; Customer risk scoring and transaction monitoring rules and models for AML, KYC; Business Intelligence, Data Visualization for risk assessment, data reporting and KPI dashboards; Exploratory data analysis including empirical data distributions, data reconciliation, missing data imputation, and outlier analysis; Statistical analysis including sampling and supervised and unsupervised machine learning; Analytical programming using SQL,SAS, Python, Spark and Hadoop Ecosystem, VBA in Excel, XML. Applicants submit resumes at https://jobs.citi.com/. Please reference Job ID # 26971221. EO Employer.

Wage Range: $130,449.69 to $180,218

Job Family Group: Risk Management

Job Family: Model Development and Analytics

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Job Family Group:

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Job Family:

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Time Type:

Full time

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Primary Location:

Tampa Florida United States

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Primary Location Full Time Salary Range:

In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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Anticipated Posting Close Date:

Aug 03, 2026

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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

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