Strategic Analytics [Multiple Positions Available]

JPMorganChase•Columbus, OH

1d•Onsite

About The Position

The position involves developing and optimizing fraud screening and acquisition strategies for deposit accounts to reduce fraud losses and enhance decision rule performance. It requires analyzing large-scale datasets to identify emerging fraud patterns and deploying adaptive countermeasures. Key responsibilities include creating and maintaining internal datamarts for improved data accessibility, building interactive dashboards and automated reports using various tools to enhance executive visibility into fraud KPIs, and analyzing fraud activity across digital and branch channels. The role also entails collaborating with Data Science and Model Risk teams to train, validate, and monitor machine learning models, conducting A/B testing and other analytical methods to evaluate fraud mitigation strategies, and ensuring compliance with regulations like FCRA. Furthermore, the individual will partner with cross-functional teams to address fraud-related process gaps, conduct exploratory data analysis to identify trends, and present fraud strategy outcomes and loss trend analyses to senior executives to influence decision-making.

Requirements

Master's degree in Information Technology, Analytics, or related field of study plus three (3) years of experience in the job offered or as Strategic Analytics Associate, Risk Architect, Data Analyst, or related occupation.
Alternatively, a Bachelor's Degree in Information Technology, Analytics, or related field of study plus five (5) years of experience in the job offered or as Strategic Analytics Associate, Risk Architect, Data Analyst, or related occupation.
Three (3) years of experience with analyzing large-scale datasets with SAS and SQL to identify fraud patterns.
Three (3) years of experience with creating and maintaining datamarts with SQL and SAS.
Three (3) years of experience with building dashboards and automated reports using Excel, Tableau, and PowerPoint.
Three (3) years of experience with analyzing fraud activity and trends across digital and branch channels.
Three (3) years of experience with conducting A/B testing, uplift modeling, segmentation, and hypothesis testing in SAS and SQL.
Three (3) years of experience with partnering with cross-functional teams to enhance processes and implement risk controls.
Three (3) years of experience with conducting exploratory data analysis (EDA) and trend mining using SAS and SQL.
Three (3) years of experience with presenting data-driven insights and analyses to senior executives to influence decision-making.
Three (3) years of experience with data mining, data transformation, and segmentation techniques using SQL and visualization tools.
Three (3) years of experience with exploratory data analysis (EDA) to identify trends and inform strategic risk roadmaps.
Three (3) years of experience with using Excel including VBA and Tableau to monitor trends.

Responsibilities

Develop and optimize fraud screening and acquisition strategies for deposit accounts focusing on reducing fraud losses and enhancing decision rule performance.
Analyze large-scale datasets to identify emerging fraud patterns, deploying adaptive countermeasures and targeted risk strategies.
Create and maintain internal datamarts, improving data accessibility and enabling rapid deployment of fraud solutions across initiatives.
Build interactive dashboards and automated reports using Excel, Tableau, and PowerPoint to enhance executive visibility into fraud KPIs and operational risk metrics.
Analyze fraud activity and trends across digital and branch channels, supporting the Deposit Fraud Risk portfolio through advanced data transformation and modeling.
Collaborate with Data Science and Model Risk teams to train, validate, and monitor machine learning models, ensuring model integrity and compliance with governance standards.
Conduct A/B testing, uplift modeling, segmentation, and hypothesis to evaluate fraud mitigation strategies.
Ensure compliance with regulations like the Fair Credit Reporting Act (FCRA) by performing adverse action reconciliation and supporting audit documentation.
Partner with Product, Compliance, Marketing, and Engineering teams to address fraud-related process gaps, enhancing onboarding workflows with embedded risk controls.
Conduct exploratory data analysis (EDA) and trend mining to identify fraud trends and inform strategic risk roadmaps.
Present fraud strategy outcomes and loss trend analyses to senior executives through data-driven presentations and summaries, influencing decision-making aligned with evolving fraud and risk trends.