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Senior Quant Analytics Associate - AML Alert Scoring Job in Cleveland, Ohio US
Monster
 
 
 
 

Job Summary

Company
KeyBank NA
Location
Cleveland, OH
Industries
Government and Military
Job Type
Full Time
Employee
Years of Experience
2+ to 5 Years
Job Reference Code
53554719

Senior Quant Analytics Associate - AML Alert Scoring

About the Job

Location:
127 Public Square - Cleveland, Ohio 44114

ABOUT THE JOB (JOB BRIEF)
The Senior Quantitative Analytics Associate is responsible fordevelopment, testing, and tuning of in-house AML Transaction Monitoring Alert Scoring modelsusing statistics, advanced mathematical techniques, and/or computer science. The Senior 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?". Projects undertaken by the Senior Quantitative Analytics Associate are often broad in scope across multiple business segments and involve model building / maintenance and "connecting the dots" between analyses, conclusions, partner needs, and/or strategy. Success factors include: designing advanced modeling approaches and developing / modifying existing models to meet changing business needs or in response to trends and strategy; exercising functional knowledge in analytical programming languages, data literacy, and model development to deliver predictive analysis to inform business problems; leading conversation with partners, delivering the right message and translating complex theories and ideas into easy-to-understand language; and serving as an emerging leader and role model across team.ESSENTIAL JOB FUNCTIONS

Create and leverage models, inferential statistics and prescriptive analysis to proactively address compliance needs; including model development, ongoing monitoring and validation activities related to AML Alert Scoring
Use critical thinking to develop insights and deliver predictive analysis that answers business problems related to "what will happen next?"
Navigate model approval process as needed
Conduct testing and analysis to determine optimal settings for the Alert Scoring models
Develop the design and/or testing of the Alert Scoring models; including inputs, methodologies, processing, ongoing monitoring and periodic tuning
Explore new methods for ensuring satisfactory output from the Alert Scoring models
Develop and advise on the development of new models to improve our monitoring program, including machine learning and RPA solutions
Research, compile and evaluate large sets of data to assess 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
Recommend solutions based on understanding of the context, connections and conclusions; employ innovative techniques to drive model efficiencies (reducing false positives)
Make continuous improvements to data procedures, including data efficiency
Promote increased efficiency of data analysis by advocating clear data requirements
Recommend best analysis method for the situation
Perform writing, editing, and review of powerpoint presentations, spreadsheets and written reports pertaining to modeling activities
Be an emerging leader across the team: Serve as a role model to others; provide input to work product of junior staff

REQUIRED QUALIFICATIONS

Master's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 3 years of relevant experience; or Bachelor's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 5 years of relevant experience
Significant experience developing, validating and tuning decision tree and logistic regression models in a financial setting
Experience developing, validating and tuning AML transaction monitoring and prioritization/scoring models
In-depth understanding of BSA, AML, and Model Risk Management regulatory requirements, technology, and data analysis best practices to guide decision making and execution of screening technology
Strong problem solving, critical thinking and analytical skills with the ability to develop and implement monitoring processes
Ability to define and communicate key risk metrics, dashboards and analytics for senior management and executive reporting; translate technical observations to a non-technical audience
Excellent verbal, written and visual communication skills
Experience designing, implementing and documenting statistical tests
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
Ability to select and retrieve data including unstructured data retrieval, archival, and ETL
Experience developing and implementing machine learning models
Curious mind - able to identify new areas where modeling and analytics could help improve the Compliance program
ACAMS or similar certification

Role is open to remote work

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 .

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

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