Lead Analyst

Role Overview

• Guide the evaluation and refinement of underwriting criteria by applying A/B testing and regression techniques to credit scoring models. Ensure policies effectively differentiate between risk segments to minimize default rates while maintaining growth targets.
• Partner with Business Units to develop and test pricing strategies. Focus on the intersection of market positioning and long-term customer repayment behavior to ensure sustainable portfolio health.
• Utilize real-time repayment data to identify opportunities to adjust policies—tightening or loosening credit barriers based on shifting macro-economic or cohort-specific trends.
• Serve as a bridge between data science and business units, evaluating all new growth initiatives against the organization’s risk appetite and long-term financial performance.
• Develop and execute advanced data models to solve complex business problems, moving beyond descriptive reporting into prescriptive strategy.
• Design and manage high-impact dashboards (Tableau, Looker, or Power BI) that track KPIs and "early-warning indicators" of credit stress, enabling senior managers to make rapid, informed choices.
• Work with engineering teams to optimize data pipelines and workflows, ensuring that the data used for underwriting and pricing is accurate, low-latency, and scalable.
• Drive the definition and monitoring of success metrics that align business operations with financial sustainability and operational efficiency.
• Own the full lifecycle of complex analytical projects, ensuring they are delivered on time, within scope, and across multiple departmental stakeholders.
• Apply business process expertise to provide actionable recommendations that connect technical insights with field-level execution.

Requirements

• A bachelor’s or master’s degree in data science, business analytics, computer science, or a related quantitative field.
• 7+ years of experience in business intelligence or strategic evaluation, with a strong preference for candidates with a background in Credit Risk, Fintech, or Financial Services.
• Proven track record of designing and deploying automated underwriting engines that combine machine learning models with heuristic business rules to optimize portfolio ROI.
• Proficiency in SQL is a must, Python an added advantage.
• Prior experience in Project Management.
• Experience in data visualization tools like Tableau, Looker, or Power BI to create compelling, actionable insights.
• A strong business mindset with the ability to understand and address cross-functional business problems and strategic opportunities.
• Strong statistical understanding and the ability to apply statistical methods and models like Price Elasticity Modeling to solve business problems and inform decision-making.
• Exceptional storytelling and communication skills, with a demonstrated ability to convey insights to both technical and non-technical audiences.
• Experience with cloud platforms (AWS, GCP, Azure) is a plus but not required.

Tech Stack

• AWS
• Azure
• Cloud
• Google Cloud Platform
• Python
• SQL
• Tableau

Benefits

• Professional growth in a dynamic, rapidly expanding, high-social-impact industry
• An open-minded, collaborative culture made up of enthusiastic colleagues who are driven by the challenge of innovation towards profound impact on people and the planet.
• A truly multicultural experience: you will have the chance to work with and learn from people from different geographies, nationalities, and backgrounds.
• Structured, tailored learning and development programs that help you become a better leader, manager, and professional through the Sun King Center for Leadership.