FCC Model Analyst

JOB SUMMARY: The Model Analyst will be responsible for supporting the Financial Crimes Compliance (“FCC”) business units through the utilization of technical and business knowledge to assist with model validations, maintain and update model documentation, recommend solutions that solve business problems and reporting needs, amongst other skill sets. This includes identifying and defining data analytics needs as well as the structuring and analysis of data from multiple source systems for the purposes of creating and maintaining reporting (e.g. visual and flowchart modeling).ESSENTIAL DUTIES AND RESPONSIBILITIESAssist in the maintenance of formal procedures and model documentationAssist with model performance monitoring, including validation and the preparation of model validation reports and related supporting technical documentsPrepare reports in a manner that is clear and comprehensible to FCC supervisors/managers, internal auditors and regulatory examinersDevelop and maintain technical expertise of model functionality including release and upgradesEnsure that FCC Data Analytics Manager is apprised of any model issues and maintain status reportingAssist FCC stakeholders in conducting validations, performance monitoring and other system testingCreate and execute effective challenges for modeling assumptions, inputs, conceptual soundness and theory, developmental evidence, implementation and outputsIdentify process gaps and recommend new opportunities for process improvement through the use of quantitative analyticsApply statistical techniques to interpret risk and develop solutions for business consumptionEnsure that operational reports are complete and provide accurate data to enable business functions to carry on day-to-day operationsSupport the data mining, reporting and general analytics needs of the FCC departmentAbility to recognize and communicate the regulatory and policy driven use of FCC models, tools, and utilitiesSupport the development of innovative approaches and best practicesCommunicate production issues with key stakeholders such as business lines, FCC management team, and the IT DepartmentMaintain working knowledge of Bank system platformsCoordinate, develop and/or review exam and audit deliverablesHandle a large workload with the ability to complete the tasks correctly and efficiently within the designated timeframes; exercise discretion in setting prioritiesPerform any other assignments as directed by managerPossess commercial awareness of banking and BSA/AML, OFAC and Fraud risksAdheres to and complies with applicable, federal and state laws, regulations and guidance, including those related to anti-money laundering (i.e. Bank Secrecy Act, US PATRIOT Act, etc.).Adheres to Bank policies and procedures and completes required training.Identifies and reports suspicious activity.QUALIFICATIONSEducationBachelor’s Degree in Computer Science, Data Analytics, Data Science, Business Analysis or a related field requiredExperience4-6 Years working with data modeling, software implementation, enhanced reporting analytics and/or related experience in financial services data analysis and/or application development required2-3 years of experience as a model analyst or similar position working directly with BSA, OFAC and/or Fraud modelsExperience with BSA/AML model management including scenario development, segmentation and threshold tuning; OFAC models including matching algorithms and fuzzy logic and Fraud models including wire, check, online banking and RTP modelsLicenses and CertificationsCertified Anti-Money Laundering Specialist (CAMS) preferred orAnti-Money Laundering Certified Associate (AMLCA) preferredCertified Fraud Examiner (CFE) preferredCertified Financial Crimes Investigator (CFCI) preferredKnowledge, Skills, and AbilitiesFamiliarity with model vendors such as Actimize, Fircosoft and FiservMastery of analytic and data visualization tools such as SAS, SQL, Adobe Analytics (formerly Omniture Site Catalyst), Tableau, IBM Digital Analytics (formerly Coremetrics), Google Analytics, Webtrends, Python or R, etc.Ability to multitask, meet deadlines, manage competing demands/multiple projects, maintain a strong sense of urgency and follow through in addressing issuesStrong verbal and written communication skills and ability to communicate technical information to non-technical audiencesMaintains strong attention to detail in high-pressure situationsSolid understanding of data warehouse and dimensional modeling conceptsAdditional InformationCandidates residing in locations within BankUnited’s footprint may be given preference.

• Bachelor’s Degree in Computer Science, Data Analytics, Data Science, Business Analysis or a related field required, * 4-6 Years working with data modeling, software implementation, enhanced reporting analytics and/or related experience in financial services data analysis and/or application development required
• 2-3 years of experience as a model analyst or similar position working directly with BSA, OFAC and/or Fraud models
• Experience with BSA/AML model management including scenario development, segmentation and threshold tuning; OFAC models including matching algorithms and fuzzy logic and Fraud models including wire, check, online banking and RTP models

Licenses and Certifications

• Certified Anti-Money Laundering Specialist (CAMS) preferred or
• Anti-Money Laundering Certified Associate (AMLCA) preferred
• Certified Fraud Examiner (CFE) preferred
• Certified Financial Crimes Investigator (CFCI) preferred

Knowledge, Skills, and Abilities

• Familiarity with model vendors such as Actimize, Fircosoft and Fiserv
• Mastery of analytic and data visualization tools such as SAS, SQL, Adobe Analytics (formerly Omniture Site Catalyst), Tableau, IBM Digital Analytics (formerly Coremetrics), Google Analytics, Webtrends, Python or R, etc.
• Ability to multitask, meet deadlines, manage competing demands/multiple projects, maintain a strong sense of urgency and follow through in addressing issues
• Strong verbal and written communication skills and ability to communicate technical information to non-technical audiences
• Maintains strong attention to detail in high-pressure situations
• Solid understanding of data warehouse and dimensional modeling concepts