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Sr. Quant Analytics Manager in Buffalo, NY at KeyBank

Date Posted: 2/23/2021

Job Snapshot

  • Employee Type:
    Full-Time
  • Location:
    Buffalo, NY
  • Date Posted:
    2/23/2021

Job Description

Working as a member of the Financial Crimes Risk Surveillance (FCRS) team within Financial Crimes Governance (FCG), Senior Quant Analytics Manager is responsible for ensuring the overall effectiveness of the advanced Machine Learning (ML) models utilize for BSA/AML and OFAC surveillance. The candidate is expected to partner and collaborate with Risk Modeling & Analytics (RM&A), Enterprise Security Services (ESS), and various other teams to ensure robust model design by making sure its structure, inputs, and parameters are sound and comprehensive from AML and OFAC perspective. The candidate independently leads the review of the Model’s overall suitability for its intended use and purpose, evaluation of the model’s theoretical framework, and assessing data and assumptions used for model development. The candidate is expected to communicate technical theories, observations, and models to a non-technical audience in a clear and concise manner. The candidate in this role is expected to have advanced mathematics, data science, and business knowledge and is expected to act as a strategic advisor and creditable partner who works across teams for addressing business problems with innovative and effective solutions. The candidate is responsible for guiding modeling practices, methods, and techniques as well as influencing data strategy with a focus on leveraging both current and emerging technologies for solving business problems.

Essential Job Functions
  • Responsible for assessing BSA/AML and OFAC models for conceptual soundness; Assess model’s overall suitability for its intended use and purpose, model’s theoretical framework, data, and assumptions made during the development to ensure its relevance.
  • Responsible for evaluating statistical and analytical approaches and testing used for model development, and benchmark methodologies. Evaluate ongoing tuning and calibration plans for ongoing model effectiveness testing. Assess and understand risks and contingency plans; when necessary perform independent statistical analysis, benchmarking, and other forms of testing.
  • Responsible for identifying and gathering the relevant and quality data sources required to fully answer and address the problem; Provides strategic solutions through exploratory data analysis (EDA).
  • Provides effective challenges in the design and implementation efforts to ensure the final model meets the regulatory expectations. Translates recommendations into communication materials to effectively present to mid-to-upper level management.
  • Provide oversight in the development of tools and techniques for monitoring model performance and integrity post-production, and for identifying any quantitative or qualitative risk associated with the model.
  • Responsible for creating and maintaining complete & clear documentation of the Modeling and Analytic activities, as well as the presentation of insights and recommendations to senior leadership
  • Responsible for responding to inquiries from internal and external validators, auditors, and regulators. Responses include but are not limited to explaining models and solution processes clearly, as well as addressing any official findings and/or recommendations.
  • Responsible for collaborating and partnering at all levels of the organization; guides, advises, challenges, and influences to drive organizational impact.
  • Responsible for leveraging a vast amount of structured and unstructured data to extract actionable business insights. Direct the data gathering, data processing, and data mining of large and complex datasets. Provide leadership in the development of algorithms using advanced mathematical and statistical techniques like machine learning to identify unusual behavior patterns. Guide others on data modeling methods/techniques.
  • Ability to execute an analytics process from start to finish from problem specification through to a solution. Collaborate and partner with Model Developers, AML Risk Experts, Data Analysts, Architects, and Engineers for delivering data-driven solutions for the business.
  • Utilize predictive modeling and other advanced techniques for identifying innovative and effective solutions for detecting potential money laundering activities

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 6 years minimum 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 7 years of relevant experience.
  • 5+ years of Applied Data Analysis, Model Development, Model Testing & Tuning experience. Hands-on work experience with SQL or SAS, and Python or R for developing Machine Learning (ML) algorithms and solutions for solving real-world problems; Prior BSA/AML or OFAC modeling experience preferred.
  • 2+ years of experience in machine learning solution delivery in solving business problems. Hands-on experience in the machine learning (ML) and Artificial Intelligence (AI) areas: Natural Language Processing (NLP), Deep Learning, Anomaly Detection, and Graph-based techniques
  • Solid expertise using core statistical learning algorithms including linear models, decision tree, random forest, clustering/segmentation, dimension reduction, ensemble models, SVMs, and kernel methods to analyze large structured and unstructured datasets
  • Mastery in programming and database language skills. Knowledge of and ability to leverage traditional databases, cloud-based computing, and distribution computing. Advance knowledge and experience in reporting & visualization Tools (e.g. Tableau, Qlikview, PowerBI, OBIEE), and Microsoft Office suite
  • Knowledge of and ability to establish standards and best practices; forecast future modeling tools/techniques. Identify, employ, and evangelize emerging techniques from industry/research.
  • Highly skilled at Influencing data and machine learning strategy. Lead discussions about the pros/cons of its applications with senior leadership. Lead work efforts from conception to delivery with minimal supervision.
  • Highly skilled at documentation and communication of analytics and modeling. Translate technical observations to a non-technical audience. Communicate observations to senior executives.
  • Knowledge of banking laws and regulations with emphasis on BSA, AML, and OFAC,
  • risk identification and mitigation.
  • Knowledge of banking products and services.
  • Experience in handling 3rd party model reviews/challenges (e.g. Exams and Audits)
  • Certified Anti-Money Laundering Specialist (CAMS) or willingness to pursue it.

Expected Competencies
  • Leadership: The candidate in this role does not have any immediate direct reports but expected to manage the integration of activities within or outside of teams; Serve as a role model for the broader team. Promotes the group and their capabilities to stakeholders and provides thought leadership.
  • Partnering/Influencing: Considered a strategic advisor to senior management and executive level business partners; Able to effectively collaborate and partner at all levels of the organization; Sought after as credible thought leader; Leverages subject matter expertise to guide, advise, challenge, and influence at all levels


FLSA STATUS:Exempt

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.

46142BR

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