Senior Credit Risk Analyst

Role Overview

The Senior Credit Risk Analyst is responsible for leading the design and execution of credit risk analytics, scoring model development, and risk policy refinement to support Kifiya’s lending partnerships. This role provides advanced analytical capability to help Kifiya develop data-backed lending solutions and de-risk credit portfolios in emerging and underserved markets.
Acting as the technical anchor of the credit risk function, the Senior Analyst works closely with product, data science, and banking partners to interpret portfolio performance, validate credit models, and ensure policy alignment with performance. They will lead in translating data into risk insights, designing scoring enhancements, and supporting credit decision frameworks for digital and embedded lending products.

Key Responsibilities

1. Credit Risk Analytics & Scoring Design

• Lead the development and enhancement of credit scoring models, including segmentation, cut-off setting, and back-testing.

• Analyse borrower performance data and recommend changes to credit rules, pricing, or loan limits.

• Work with data science teams to ensure AI/ML models are accurate, interpretable, and monitored for drift or bias.

2. Portfolio Risk Monitoring & Early Warning

• Monitor portfolio health across partners, segments, and cohorts using delinquency, vintage, and exposure analysis.

• Design and refine early warning triggers for deteriorating segments or loan types.

• Support portfolio stress testing under macroeconomic or behavioural scenarios.

3. Credit Policy & Product Support

• Provide analytical support to the design of credit policies, underwriting standards, and exception handling rules.

• Collaborate with product and credit operations teams to ensure credit design aligns with risk appetite and scoring models.

• Assist in preparing decision memos for new product launches or policy changes.

4. Reporting & Performance Insights

• Develop and maintain credit performance dashboards, loss forecasting models, and model validation reports.

• Present findings to credit managers and contribute to quarterly review memos.

• Maintain documentation for scoring, analytics, and risk assumptions.

5. Stakeholder Engagement & Support

• Work with banking partners, regulators, and auditors to explain scoring methodology and portfolio risk controls.

• Support internal and external queries on model performance, risk assumptions, and credit metrics.

Educational Background

• Bachelor’s degree in Statistics, Economics, Data Science, Finance or a related field.
• Master’s degree or technical certifications in quantitative finance, analytics, or data science is preferred.

  Professional Experience

• 5–7 years of experience in credit risk analysis, credit modelling, or portfolio analytics.
• Experience in digital lending or fintech is preferred (not heavily banking-focused).
• Exposure to MSME, consumer, or agricultural credit portfolios is an added advantage

Technical Skills

• Strong statistical and analytical modelling skills, including logistic regression, decision trees, scorecard development.
• Proficiency in Python, R, SQL, or other statistical tools.
• Ability to interpret and work with data from lending platforms, CRBs, and alternative data sources.
• Working knowledge of credit policy frameworks and risk-adjusted pricing