Compliance Quantitative Data Analyst

Full Time
United States
Posted
Job description
Job Description

The Compliance Quantitative Data Analyst (“QDA”) plays a critical role developing and supporting the Netspend Compliance Department’s data needs, specifically including Anti Money Laundering (“AML”), Customer Identification Program (“CIP”), Compliance Testing, and Distributor Due Diligence (“DDD”). The Compliance Quantitative Data Analyst will play a key role in the following:
  • AML Model Risk Development, Management, and Validation
  • Developing and Maintaining Compliance Data Sources (SQL, Snowflake)
  • Developing and Maintaining Compliance Data Reports (SQL Query, Snowflake Query, Excel Charts, Tableau Charts, Qlik Charts)
  • AML Risk Assessment (SQL, Tableau, Excel, Qlik)
  • AML, CIP, DDD, and Compliance Testing Data & Data Models
  • AML Customer Risk Scoring
  • Customer Due Diligence Data Analysis
  • DDD Risk Assessment & Risk Scoring
  • OFAC, Sanctions, and Negative News Name Matching Fuzzy Logic and Data Analysis
  • Ad Hoc Data Analysis
The job demands include data mining, data aggregation, and development of models that highlight compliance and AML risk, providing recommendations for AML risk management strategy and monitoring rules. Analytical requirements also include analysis of business processes to maintain efficiencies; analysis of compliance with regulatory requirements; bench mark analysis of expected customer behavior, as well as, producing sample data for internal testing and developing ad hoc reporting as requested from the Compliance department. This position reports to the Director of AML/BSA Compliance.
The tools currently used in this role include, but are not limited to: SQL, Snowflake, Excel, Word, Tableau, Qlik, Python.
Responsibilities:
  • Develop/Test/Monitor/Validate/Rationalize AML Rules to Monitor Customer and Distributor Transaction Activity
    • Develop, test and deploy monitoring rules in AML transaction monitoring system(s). Evaluate feedback from analysts, bank partners and auditors to tune and optimize alert rules, policies and procedures.
    • Test and validate the performance of alert rules and false positive ratios (FPR) and provide recommendations for rule enhancements.
    • Document all rule changes and procedures surrounding the decisions to create or modify monitoring rules.
    • Generate data to enable monitoring of team and individual performance metrics.
  • Interface with Netspend business owners, bank partners, auditors to validate business requirements, share knowledge, and manage expectations related to changes in policy, process, procedure or requests for analysis.
  • Data analysis includes building or querying existing data sets to:
    • Identify trends, patterns, rules associated with financial crimes.
    • Provide complex data analysis to identify, troubleshoot, resolve and/or escalate trends that will impact transaction monitoring.
    • Utilize data mining techniques to identify AML Risks.
    • Analyze business process flow and identify areas of abuse, misuse, waste, inefficiency.
    • Review business process flows for areas of efficiency opportunities.
    • Provide reporting and analysis of regulatory compliance for internal and external auditors and partners, as well as, adherence to internal policies and controls.
    • Generate reporting and analysis to provide baseline levels of customer behavior and set upper and lower bounds on suspicious or unusual behavior.
    • Develop ad hoc reporting to answer immediate business needs.
    • Develop recurring and automated dashboard reporting.
    • Document and present analytical methodologies used.
    • Present clear and concise solutions/results to business leaders and management.
  • Interface with Compliance business owners to validate business requirements, share knowledge, manage expectations related to changes in policy, process, procedure or requests for analysis.
  • Create predictive and other analytically derived models for assessing AML risks.
  • Quantifies value of new data sources, data elements, and alternative modeling approaches.
  • Identifies and recommends new modeling and analytics opportunities.
  • Translates high level business objectives into quantifiable analysis tasks.
  • Data analysis for millions of accounts per year and millions of transactions per day.
Skills/Education/Experience:
  • Advanced degree (Masters or Doctoral Level) in Statistics, Mathematics, or related field that provides an academic background for statistical modeling is preferred;
  • Advanced experience with statistical modeling tools (Python or R preferred);
  • Advanced experience with regression analysis, decision trees, clustering and other statistical modeling;
  • Advanced SQL coding skills required; ability to develop new functions and procedures and automate processes preferred;
  • Solid understanding of relational databases and confident extracting data and building data sets from relational database;
  • Able to extract, transforms and load (ETL) datasets from various sources;
  • Experience with graphical reporting tools (Tableau/Qlik) a plus;
  • 2-3 years of experience working as a data analyst. Experience in prepaid, credit or banking industry a plus.;
  • Able to work with little direct supervision once ownership of a project or task has been assigned;
  • Able to execute multiple analytic projects at high level of quality on tight business timetable;
  • Able to work effectively on cross-functional business team composed of people with diverse backgrounds, some of whom are non-technical;
  • Strong presentation development and writing skills (e.g. proficient in Microsoft Excel, PowerPoint and Word, especially creating summary tables, charts and pivot tables with Excel) Advanced technical and business critical writing skills a plus;
  • As provided in NetSpend's Background Check policy, eligible candidates may be subject to drug, criminal history, and credit checks, which will be conducted and used in accordance with applicable local, state, and federal laws.

This position is eligible to be considered for remote hiring anywhere in the USA.

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