Data Analyst
Saxon Global
Key Responsibilities
Data Analysis & Insight Generation
Data Analysis & Insight Generation
- Perform 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.
- Strong 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.
Vacancy posted 2 days ago
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