Data AnalyticsThis Data Analytics role is responsible for designing, implementing, and monitoring data-driven analytical tools and insights that support the acquisitions and collections lifecycle within Risk Management. The position focuses on transforming complex data into actionable insights that inform credit strategy, collections effectiveness, recovery performance, and pricing decisions.The role applies strong analytical, statistical, and quantitative techniques—leveraging SQL, advanced analytics tools, and emerging machine-learning methods—to solve business problems aligned with risk management objectives. The Data Analyst partners closely with cross-functional stakeholders and global Risk teams to ensure best practices are followed in scoring, pricing, and performance monitoring, while also supporting governance and compliance activities, including internal control requirements where applicable.Key ResponsibilitiesPerform in-depth quantitative and analytical analysis using advanced techniques such as segmentation, pattern recognition, trend analysis, text mining, and supervised or unsupervised modeling.Analyze large, multi-source datasets to uncover insights related to credit risk, customer behavior, collections performance, and recovery outcomes.Translate analytical findings into clear, actionable recommendations that support risk-based acquisition, collection, and recovery strategies.Extract, cleanse, validate, and transform data to support ad-hoc analysis, recurring reporting, and analytical model inputs.Ensure data quality, consistency, and accuracy across multiple internal and external data sources.Serve as a trusted, data-driven advisor to internal business partners, supporting strategic and operational decision-making through evidence-based insights.Communicate complex analytical concepts and results clearly to both technical and non-technical stakeholders, including leadership.Support the development, testing, implementation, documentation, and ongoing monitoring of internally developed analytics and machine-learning models in accordance with established policies and governance standards.Produce and maintain quarterly performance and monitoring reports for risk, collections, and recovery models, tracking accuracy, stability, and business impact.Partner with external vendors to evaluate, test, implement, and monitor third-party scoring models and analytical solutions.Assist with vendor performance monitoring, documentation, and quarterly compliance reporting.Stay current with emerging analytics tools, methodologies, and technologies, assessing their applicability to risk analytics use cases.Contribute to the continuous improvement of analytics processes, reporting, and tooling within Risk Management.Required Skills & QualificationsStrong analytical, quantitative, or technical finance background with working knowledge of risk management concepts; experience in automotive or financial services is strongly preferred.Advanced proficiency in SQL and relational databases; experience with SAS or similar analytical tools is highly desirable.Experience using Python and applying analytical or machine-learning techniques for risk, collections, or recovery analytics is a plus.Solid understanding of data validation, statistical analysis, and performance monitoring.Strong written and verbal communication skills, with the ability to convey analytical insights to diverse audiences.Demonstrated experience collaborating on cross-functional or cross-departmental initiatives.Familiarity with credit decision engines, scorecards, or model governance frameworks is highly desirable.