Lead Quantitative Analytics Associate - AML


127 Public Square - Cleveland, Ohio 44114


Under some supervision, the Lead Quantitative Analytics Associate is primarily responsible for testing and tuning of Anti-Money Laundering (AML) vendor and in-house Transaction Monitoring models using statistics, advanced mathematical techniques, and/or computer science to develop and validate predictive and machine-learning models for specific business needs. The Lead Quantitative Analytics Associate leverages advanced mathematical knowledge and analysis to provide solutions to predictive and prescriptive questions such as "What will happen next?" and "What will we do?". Often large, in-scope, projects undertaken by the Lead Quantitative Analytics Associate involve self-directed data analysis and model building in response to a problem statement proposed by a business partner. Success factors include: timely and effective completion of tasks assigned by manager with manager and/or peer guidance; exercising functional knowledge in analytical programming languages, data literacy, and model development; effective communication of insights and data to peers; and developing work autonomy and problem-solving.


* Create and leverage models, inferential statistics, and prescriptive analysis to proactively address compliance needs; including model development, model tuning, ongoing monitoring, and validation activities related to AML
* Develop and advise on the development of new models to improve our monitoring program, including statistical inference, and machine learning
* Conduct testing and analysis to determine optimal model settings for the AML models (i.e. Mantas scenarios), including "Above-the-line" and "Below-the-Line" testing
* Use critical thinking to use the right approach for each problem statement
* Develop the design and/or testing of vendor and in-house models; including inputs, methodologies, processing, ongoing monitoring, and periodic tuning
* Explore new methods for ensuring satisfactory output from AML vendor and in-house models
* Research, compile and evaluate large sets of data to assess the quality and determine suitability for model building
* Adhere to a strict ongoing monitoring schedule; provide analytical results to Model Owners, and assist in evaluating model reliability/performance
* Make continuous improvements to data procedures, including data efficiency
* Promote increased efficiency of data analysis by advocating clear data requirements
* Perform writing, editing, and review of PowerPoint presentations, spreadsheets, and written reports pertaining to modeling activities


* Bachelor's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 2 years of relevant experience; or Master's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 1 years of relevant experience
* Understanding of BSA, AML regulatory requirements, technology, and data analysis best practices to guide decision making and execution of screening technology
* Experience designing, implementing, and documenting statistical tests
* Experience developing, validating, testing, implementing, and tuning Machine Learning models
* Intermediate to advanced SQL query skills
* Intermediate to advanced skills in a statistical coding language - SAS or Python strongly preferred
* Understanding the Pros / Cons of competing analysis methods
* Understanding and ability to leverage cloud-based computing, including Google Cloud
* Excellent verbal, written, and visual communication skills
* Curious mind - able to identify new areas where modeling and analytics could help improve the Compliance program

Preferred Qualifications:

* Experience working with AML-related vendor tools, including Mantas and/or Actimize
* Experience developing, validating, and tuning models for AML transaction monitoring
* ACAMS or similar certification

KeyCorp is an Equal Opportunity and Affirmative Action Employer committed to building a diverse, equitable and inclusive culture. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status or other protected category.

Qualified individuals with disabilities or disabled veterans who are unable or limited in their ability to apply on this site may request reasonable accommodations by emailing HRCompliance@keybank.com.
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