(USA) Staff Data Analyst, AML

Position Summary...

What you'll do...

The Staff Data Analyst, Anti-Money Laundering (AML) will help identify AML detection scenarios, provide analytics support to improve AML and fraud transaction monitoring and screening systems, customer segmentation, coordinate the implementation of AML and fraud scenarios, which detect financial crime and create statically representative samples to ensure that risk is not missed below the threshold. Will conduct research to benchmark industry best practices and leverage technological solutions to better manage risk within area of focus. Create the data for reporting on key performance metrics for compliance programs for area of focus.

You'll make an impact by:

• Creating statistical representative samples for ATL/BTL testing in order to validate that the transaction monitoring model is effective and functioning accordingly
• Developing mathematical or statistical theory to interpret customer KYC data and historical transaction data to group customers and non-customers into segments in order to monitor their activity in the correct thresholds
• Identifying trends of historical transactional data for AML and fraud monitoring
• Analyzing clusters and present the information in data visualization tools
• Processing large amount of data for statistical modeling and graphic analysis
• Performing model validation, memorializing model selection rationales and defined assumptions.
• Developing and test experimental designs, sampling techniques, and analytical methods in order to monitor new typologies and emerging risks.
• Developing data mining methodologies, including logistic regression, random forest, xgboost and Bayesian networks
• Developing models involving tuning, calibration, segmentation and optimization

You'll sweep us off our feet if

• You have strong knowledge of mathematics particularly statistics.
• You have the ability to code using R or Python and have working knowledge of at least one of the following: SAS, Matlab, R, Python, SQL, VBA, etc.
• You have a proven track record to solve problems through mathematical and deductive reasoning.
• You have experience analyzing, testing and/or validating BSA/AML models, and/or OFAC sanctions screening models.
• You are familiar with implementing, testing or evaluating performance of financial crime and compliance systems.
• Proven track record of strong quantitative testing and statistical analysis techniques as it pertains to BSA/AML models, including name similarity matching, classification accuracy testing, unsupervised/supervised machine learning, neural networks, fuzzy logic matching, decision trees, etc.
• You are current with compliance rules and regulations of the FRB, SEC, OCC, FATF, FinCEN, OFAC, and familiarity with USA PATRIOT Act, BSA/AML and OFAC screening regulations.
• You have strong knowledge about model risk management and associated regulatory requirements

Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelor's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Arts, Finance or related field and 3 years' experience in data analysis, data science, statistics, or related field. Option 2: Master's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 1 year's experience in data analysis, data science, statistics, or related field. Option 3: 5 years' experience in data analysis, data science, statistics, or related field.

Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Data science, data analysis, statistics, or related field, Master's degree in Business, Computer Science, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field, Related industry experience (for example, retail, merchandising, healthcare, eCommerce), Successful completion of assessments in data analysis and Business Intelligence tools and scripting languages (for example, SQL, Python, Spark, Scala, R, Power BI, or Tableau)