Lulalend
OVERALL PURPOSE
As a Credit Risk Data Analyst, you will play a pivotal role in analysing and defining the credit risk strategies and driving growth initiatives for Lula. Working within a high-impact team, you will support three core verticals (Credit Modeling, Credit Risk Strategy, and Credit Insights) to transform complex data into actionable intelligence.
Your primary mission is to design, deploy, and modernize the sophisticated credit risk models and strategies that drive our funding decisions, ensure regulatory compliance, and maximize profitability across the credit lifecycle.
KEY RESPONSIBILITIES:
Support the development and enhancement of credit models used to inform the funding decision. These include scorecards, affordability, pricing models, take-up models and profit models.
Monitor and investigate book performance to drive growth and control credit risk.
Review and define data-driven credit risk policies, strategies, affordability design, test frameworks, offer terms and profit optimization.
THE COMPETENCIES WE’RE AFTER
A passion to drive positive change in South Africa by growing small and medium enterprises
Curiosity supported by high levels of analytical thinking/problem solving
Strong team player that helps us win as one.
Can work independently with high internal ambition.
Data access, transformation and aggregation
Data driven credit risk strategy design, deployment and tracking
Model development and monitoring will be beneficial
Understanding of credit risk management fundamentals
Understanding of small business lending will be beneficial
THE EXPERIENCE WE’RE LOOKING FOR
Must have a numerical degree (e.g. mathematics, statistics, finance, data science).
Must have at least 2 years credit risk data analytics experience.
Must have at least 2 years experience in actively using SQL in data analytics
Must have at least 2 years experience in actively using Python in data analytics
OUR TECH STACK
Azure
Snowflake
DBT
Python
SQL
Hex
GitHub
go to method of application »
Apply via company website ( ) or