DESCRIPTION:

Duties: Manage the Consumer Bank and Business Bank deposit account fraud losses through advanced analytics and reporting, identifying opportunities for loss mitigation based on fraud and authorization patterns, and leading the team in developing and implementing effective strategies. Collaborate with key Consumer Banking product owners to deliver analytics-driven insights and clear storytelling regarding emerging fraud trends and patterns. Contribute to major technical projects and programs by providing strategic and design recommendations, ensuring alignment with business objectives and that all stakeholder requirements are met. Partner with the CCB Risk Modeling team to enhance machine learning models by refining modeling techniques, identifying new predictive variables, and optimizing the model update cycle. Continually improve internal analytical methodologies and introduce industry best practices to drive enhancements in key business metrics, while fostering collaborative relationships with cross-functional partners to address complex business challenges. Identify business opportunities through comprehensive analysis, including data mining, ensuring data integrity, synthesizing findings, and effectively communicating actionable insights to senior management. Provide concise oral and written communication across various functions and organizational levels including Operations, IT, and Risk Management. Interpreting large volumes of complex data, formulating problem statements, drawing conclusions regarding risk dynamics, trends, and opportunities, and performing ad hoc analyses to deliver updates on key projects to leadership teams. Mentor and manage internal teams and coordinate with external resources such as consultants and vendors. Utilize analytics and support the adoption of machine learning within an organization to solve business problems.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Business Analytics, Project Management, Statistics, Data Science, Engineering (any) or related field of study plus 5 years of experience in the job offered or as Point of Sale Fraud Strategy, Engineer Data Science, Software Engineer, or related occupation. The employer will alternatively accept a Bachelor's degree in Business Analytics, Project Management, Statistics, Data Science, Engineering (any) or related field of study plus 7 years of experience in the job offered or as Point of Sale Fraud Strategy, Engineer Data Science, Software Engineer, or related occupation.

Skills Required: This position requires five (5) years of experience with the following: Designing, developing, and optimizing SQL queries, including stored procedures, functions, triggers, and views, to extract, transform, and reconcile large datasets from enterprise relational databases; using Python, SAS, and R in performing data acquisition, cleansing, and manipulation to support business intelligence, analytics initiatives, conduct statistical analysis, and building machine learning models including XGBoost; utilizing Python, Statistical Analysis System (SAS), and R to conduct statistical analysis and build machine learning models, including logistic regression, multivariate regression, classification, cohort analysis, associative rule mining, and predictive modeling; applying descriptive, predictive, and prescriptive analytics using SAS and Python to solve business problems and quantify benefits; designing and developing interactive reports and dashboards using Tableau, Power BI, Python, SAS, Hyperion Essbase, Excel, and PowerPoint to translate quantitative information into actionable insights for both analytic and non-analytic stakeholders.  

Job Location: 1111 Polaris Parkway, Columbus, OH 43240.

Full-Time.