WHAT WE DO

Lula is an innovative and human-focused FinTech company on a mission to help small businesses optimise their cash flow. Our purpose is to help SMEs manage their businesses better, faster, and more simply, so they can spend more time doing what they love.

If you’re looking for a new place to call ‘home’ that believes in the potential of the broader SME landscape in South Africa and a place where you’ll work with awesome people - then Lula’s the place for you!

We’re making business banking fast, human, Lula!

OUR VALUES

Collaborative - we’re a clan and work together as a team, always towards a common goal

Committed - we’re accountable and follow through no matter the challenge

Curious - we look for better ways to do things and make a positive difference

Connected - we stay close to, learn from and look to understand each other and our customers

Compassionate - we go out of our way to care about our colleagues, our customers and our community

OVERALL PURPOSE

The Lead Credit Strategy Analyst is responsible for the analytical execution of the definition of credit risk policies, credit risk strategies and credit risk optimisation. This role is the analytical lead defining Lula’s risk appetite, return hurdles, credit risk policies, affordability assessment, strategy design, test frameworks, offer terms and ultimately profit optimisation across the credit lifecycle.

The successful candidate will work closely with cross-functional teams, including the Credit Modelling Lead, Credit Underwriting, Portfolio Management, Collections, Business Development, Finance, and Data Engineering, to ensure that credit policies and strategies are optimised for both performance and compliance.

Responsibilities will include:

• Identifying expansion opportunities to grow the portfolio profitably / profit optimisation opportunities.

• Leading analytical projects to define credit policies, strategies, affordability assessments, offers (terms of business) and test frameworks across the credit lifecycle.

• Executing data driven profit optimisation decisions across the credit lifecycle.

• Working with the Data Science, Credit Underwriting, Collections and Portfolio Management teams to execute data-driven insights / strategies.

• Accountability for the implementation and performance of automated credit decisioning strategies (across multiple products, including Merchant Cash Advance and revolving credit for SMEs) in line with KPIs and Business Strategy.

• Continuously evaluating and developing data driven strategies to support funding decisions (credit risk, affordability, pricing, delinquency, and fraud detection).

• Providing input to enhance existing processes, identifying new opportunities within credit and collections teams.

• Staying updated with AI/ML trends and methodologies to identify emerging credit risks and opportunities.

• Working closely with Data Engineering to ensure required data for credit modelling, data driven strategy development and reporting is available.

• Collaborating with the Product team to prioritise and implement strategy changes.

• Leading and mentoring analysts within the Credit Data Science team, for assigned projects.

THE COMPETENCIES WE’RE AFTER

• Strategic thinker with the ability to align model development to business goals.

• Strong analytical leadership and team-building capabilities.

• Excellent communication skills, with the ability to present complex data insights to non-technical stakeholders.

• High attention to detail.

• Passion for innovation and staying ahead of emerging trends in data science and credit risk strategy design.

• A self-starter, able to take initiative and drive analytical projects from concept to implementation while ensuring usability across teams.

THE SKILLS AND EXPERIENCE WE’RE LOOKING FOR

• Bachelor’s or Master’s in Data Science, Statistics, Mathematics, or a related quantitative field.

• 8+ years of experience in data science, credit risk strategy analytics, or related roles within financial services, ideally in lending or fintech.

• Proven experience leading credit risk strategy analytics projects to implementation in a data-driven environment.

• Proficiency in programming languages like Python, R, and SQL.

• Experience working with credit risk and decisioning platforms.

• Knowledge of cloud-based environments and large data systems (AWS, Azure, etc.).