Business Intelligence Credit Lead

OVERALL PURPOSE We are seeking a highly skilled and analytically-driven Business Intelligence Credit Lead to spearhead our data-driven credit reporting, diagnostics and control framework. This pivotal role will be responsible for transforming raw data into actionable insights, enabling enhanced decision-making across our credit portfolio. The ideal candidate will possess a strong blend of technical prowess in data wrangling and automation, deep expertise in credit risk management, and the ability to drive strategic reporting initiatives. RESPONSIBILITIES WILL INCLUDE: Data Engineering & Automation for Credit Insights Design, develop, and maintain robust data wrangling and orchestration pipelines to extract, transform, and load credit-related data from various sources for reporting and analytical ingestion. Automate and schedule critical data processes to ensure timely and accurate delivery of credit insights. Develop and optimise complex SQL queries for data extraction and manipulation within Snowflake. Utilise Python for advanced data processing, statistical analysis and automation of reporting workflows. Advanced Data Visualisation & Reporting Lead the creation, automation, and delivery of sophisticated descriptive and diagnostic reports and Business Intelligence (BI) suites for diverse stakeholders (e.g. Credit Committee, Executive Leadership). Design interactive dashboards with advanced filters, sliders, and drill-down capabilities to empower stakeholders with self-service diagnostic analysis. Drive the adoption of best-in-class reporting tools such as Hex for compelling data visualization. Credit Risk Diagnostics & Control Framework Apply in-depth knowledge of key credit risk metrics across the entire credit risk lifecycle (origination, portfolio management, collections) within the SME funding industry. Develop and implement robust credit risk control and governance frameworks, ensuring data integrity and reporting accuracy. Implement and monitor best practice model monitoring frameworks to assess model performance and drift. Track champion-challenger strategies, providing data-driven insights on their effectiveness. Lead portfolio forecasting initiatives, including the development of methodologies to forecast and budget for key credit metrics such as delinquency, write-offs, and Expected Credit Loss (ECL). Strategic Stakeholder Engagement & Leadership Professional delivery and presentation of complex reports and insights to senior stakeholders, including the Head of Credit, Executive Committee, and Credit Risk Board. Actively participate in and provide data-driven insights to key control committees (e.g. Credit Risk Management Committee (CRMC), Portfolio Performance Review). Translate complex business requirements into clear data and reporting development specifications, achieving stakeholder buy-in and prioritization. Ability to set a clear descriptive and diagnostic reporting vision and strategic roadmap for the credit insights function. People & Analytical Mentorship Mentor and guide junior analysts in data wrangling, reporting best practices and analytical methodologies. Foster a culture of data-driven decision-making and continuous improvement within the credit team. Demonstrated experience in both self-delivery of complex analytical projects and in guiding others to achieve high-quality descriptive, diagnostic and ad hoc analytical outcomes. THE SKILLS AND EXPERIENCE WE’RE LOOKING FOR: Bachelor's degree in a quantitative field (e.g. Computer Science, Statistics, Mathematics, Actuarial Science, Engineering, or a related discipline). A minimum of 3-5 years of hands-on experience in a highly technical data analysis or data engineering role, specifically within a credit risk or financial services environment. Demonstrable expertise in Python, SQL, Data Warehousing, Data Visualisation Tools and Data Orchestration/ETL Solid understanding of credit risk management principles, metrics (e.g. PD, LGD, EAD, vintage analysis), and the credit lifecycle, preferably within the SME lending sector. Experience with credit risk model monitoring and tracking of champion-challenger strategies. Proven ability to translate business problems into analytical solutions and actionable insights. Strong communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders. #J-18808-Ljbffr