Senior Data Analyst - Fraud

Ally and Your Career Ally Financial only succeeds when its people do - and that’s more than some cliché people put on job postings. We love this stuff! We see our people as, well, people - with interests, families, friends, dreams, and causes that are all important to them. Our focus is on the health and safety of our teammates as well as work-life balance and diversity and inclusion. From generous benefits to a variety of employee resource groups, we strive to build paths that encourage employees to stretch themselves professionally. We want to help you grow, develop, and learn new things. You’re constantly evolving, so shouldn’t your opportunities be, too? Work Schedule : Ally designates roles as (1) fully on-site, (2) hybrid, or (3) fully remote. Hybrid roles are generally expected to be in the office a certain number of days per week as indicated by your manager. Your hiring manager will discuss this role's specific work requirements with you during the hiring process. All work requirements are subject to change at any time based on leader discretion and/or business need. The Opportunity In office role with weekly hybrid schedule. Ally work locations Charlotte NC or Lewisville TX The Senior Data Analyst, Fraud Data & Value Stream Analytics will support two connected priorities: building the data foundation that powers fraud detection, decisioning, investigations, and customer protection, and developing Value Stream scorecards that measure business performance and outcomes. This role will partner with Fraud, Product, Data, Technology, Architecture, Analytics, Risk, Compliance, Finance, and Operations teams to translate business needs into clear data requirements, trusted metrics, and actionable insights. The Analyst will map data across business processes and source systems, assess data quality and readiness, support real-time and batch data initiatives, and maintain documentation that improves lineage, traceability, and reuse. The role will also define and validate scorecard metrics, reconcile results to source data, produce recurring performance reporting, and explain trends and drivers to stakeholders. It is well suited for a curious, detail-oriented analyst who can connect business problems to data, communicate findings clearly, and work across teams to move complex initiatives forward. The Work Itself Key Responsibilities • Partner with business and product teams to understand fraud use cases, Value Stream objectives, business processes, decisions, and the data and measures required to support them. • Translate business needs into data requirements, source-to-target mappings, metric definitions, calculation rules, acceptance criteria, and analytical approaches. • Profile and analyze large, complex datasets to assess availability, completeness, accuracy, timeliness, consistency, and fitness for use. • Develop and maintain Value Stream scorecards, dashboards, metric dictionaries, calculation logic, targets, and recurring performance reporting. • Reconcile scorecard results to authoritative sources, investigate variances, document methodology and lineage, and clearly explain trends, drivers, limitations, and changes. • Maintain fraud data inventories, metadata, ownership, quality measures, lineage, and traceability across source and consuming systems. • Support real-time and batch data delivery through requirements validation, testing, reconciliation, production validation, and ongoing monitoring. • Communicate findings, risks, decisions, and recommendations to technical and nontechnical audiences while managing multiple priorities in a collaborative environment. Qualifications We’re Looking For • Bachelor’s degree in data analytics, information systems, computer science, statistics, mathematics, business, finance, or a related field, or equivalent work experience. • 3+ years of experience in data analysis, business intelligence, performance measurement, scorecard reporting, data management, financial services, fraud, risk, or a related discipline. • Strong SQL skills and experience querying, joining, validating, and analyzing large datasets across multiple sources. • Experience with data profiling, mapping, data-quality assessment, reconciliation, root-cause analysis, metadata, lineage, metric governance, and requirements documentation. • Experience developing and maintaining scorecards, dashboards, metric definitions, and visual analyses using Snowflake, Power BI, and Excel. • Working knowledge of data concepts such as real-time streaming, batch integration, APIs, data models, operational data stores, analytical platforms, and cloud-based services. • Strong analytical thinking, attention to detail, problem-solving, documentation, and verbal and written communication skills. • Ability to work independently, manage competing priorities, and collaborate effectively with business, product, data, and technology partners. • Experience with Python or another analytical programming language is preferred. • Experience with fraud, identity, authentication, payments, decisioning, investigations, or financial-crime data is preferred. Minimum Qualifications: • 3+ years or relevant experience • Bachelor's degree in Computer Science, Information Systems, Data Science, Data Analytics or equivalent How We'll Have Your Back Ally's compensation program offers market-competitive base pay and pay-for-performance incentives (bonuses) based on achieving personal and company goals. Our Total Rewards program includes industry-leading compensation and benefits plus additional incentives that are designed to meet your needs and those of your family so you can get the most out of your career and your life, including: Time Away: Program starts at 20 paid time off days in addition to 11 paid holidays and 8 hours of volunteer time off yearly (time off days are prorated based on start date and program varies based on full or part-time status and management level). Planning for the Future: plan for t