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.