Head of Credit Data Science Leader

4 days ago

Cape Town, Western Cape, South Africa Lula Full time
Job Title: Head of Credit Data Science

At Lula, we're on a mission to revolutionize business banking for small businesses. As our Head of Credit Data Science, you'll play a critical role in driving our credit automation strategy, ensuring our models are compliant with IFRS9 standards, and delivering world-class results.

Key Responsibilities:
  • Develop and execute a strategic roadmap for credit automation, aligning with business objectives and driving credit decisioning excellence.
  • Collaborate with the Credit Management team to define vision and goals for credit automation initiatives, ensuring seamless integration with our existing processes.
  • Identify expansion opportunities to grow our portfolio profitably, leveraging data-driven insights and credit knowledge.
  • Work closely with the Head of Credit Underwriting and Portfolio Manager to combine data-driven insights with credit expertise, driving informed decision-making.
  • Accountable for the implementation and performance of automated credit decisioning models, ensuring alignment with KPIs and business strategy.
  • Monitor and enhance automated credit decisioning models, ensuring necessary improvements and mitigating potential risks.
  • Implement and monitor controls to mitigate potential risks associated with automated credit decisions, ensuring compliance with regulatory requirements.
  • Ensure accurate and timely reporting on the performance of automated products, providing actionable insights for business stakeholders.
  • Responsible for building, implementing, and maintaining an IFRS-compliant provisioning model in collaboration with Finance and Credit Management.
  • Continuously evaluate and develop analytical models to support funding decisions, including credit risk, affordability, pricing, delinquency, and fraud detection.
  • Ensure appropriate governance for development, sign-off, and monitoring of models, ensuring transparency and accountability.
  • Provide input to enhance existing processes, identifying new opportunities within credit and collections teams, and driving continuous improvement.
  • Collaborate with the Portfolio Manager to analyze portfolio performance, identify higher-risk areas, and recommend remedies, ensuring proactive risk management.
  • Extend company data with relevant third-party and alternative sources for building analytic systems, ensuring data quality and integrity.
  • Stay updated with AI/ML trends and methodologies, identifying emerging credit risks and opportunities, and driving innovation within the team.
  • Work closely with Data Engineering to ensure required data for credit modelling and reporting is available, ensuring seamless integration with our data infrastructure.
  • Collaborate with the Product team to prioritize and drive initiatives forward, ensuring alignment with business objectives and customer needs.
  • Manage the Data/Decision Science team, including recruitment, KPI setting, and ensuring world-class delivery, driving team success and growth.
Requirements:
  • Strategic thinker with the ability to align model development to business goals, driving credit decisioning excellence.
  • Strong leadership and team-building capabilities, with a proven track record of driving team success and growth.
  • Excellent communication skills, with the ability to present complex data insights to non-technical stakeholders, ensuring seamless collaboration.
  • High attention to detail, ensuring accuracy and compliance in all modelling activities, and driving quality and integrity.
  • Passion for innovation and staying ahead of emerging trends in data science and credit automation, driving continuous improvement and growth.
  • A self-starter, able to take initiative and drive models from concept to implementation, ensuring usability across teams and driving business success.
Qualifications:
  • Grade 12 achieved.
  • Bachelor's or Master's in Data Science, Statistics, Mathematics, or a related quantitative field.
  • Advanced degree (PhD) preferred but not required.
  • 10+ years of experience in data science, analytics, or related roles within financial services, ideally in lending or fintech.
  • Proven experience leading teams and driving strategic initiatives to implementation in a data-driven environment, with a strong track record of success.
  • Significant experience in the implementation of credit risk models, scorecards, and previous accountability for the performance of these models in the credit context.
  • Strong expertise in machine learning, AI, and statistical modelling techniques, with a proven ability to drive innovation and growth.
  • Proficiency in programming languages like Python, R, and SQL, with a strong ability to drive data-driven insights and decision-making.
  • Experience working with credit risk and decisioning platforms, with a strong understanding of IFRS9 and ECL modelling.
  • Solid understanding of cloud-based environments and large data systems (AWS, Azure, etc.), with a strong ability to drive innovation and growth.

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