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 WERE LOOKING FOR:
- Bachelors 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.
OVERALL PURPOSEWe 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 decisio...
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 WERE LOOKING FOR:
- Bachelors 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.
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