Credit Risk Analyst at Shecluded

Role Overview

• We’re looking for a Credit Risk Analyst who is passionate about building strong, data-driven credit systems that unlock opportunities for women in business.
• As we continue to tackle the gender finance gap and deepen our impact, we need someone who can bring analytical excellence, sound judgment, and a commitment to maintaining a healthy, high-performing loan portfolio.
• If this is you! We want you!
• The ideal candidate is a problem-solver at heart; someone who enjoys digging into numbers, spotting patterns, and challenging assumptions to make smarter, faster credit decisions.
• They have a strong understanding of credit risk, lending processes, and portfolio dynamics, and are excited about how technology and AI can transform credit for women entrepreneurs.

Responsibilities

• Conduct thorough credit assessments and analyze borrowers’ financial statements, cash flow, and repayment capacity.
• Review loan applications, prepare credit memos, and make clear recommendations on approval or decline.
• Monitor loan portfolio performance, identify early warning signs, and support strategies to reduce default risk.
• Ensure compliance with credit policies, documentation standards, and risk management procedures.
• Prepare regular credit and portfolio reports to support decision-making by the credit and leadership teams.

What Makes You a Great Fit

• You love problem-solving and naturally think in terms of systems, probabilities, and causes.
• You have a solid grasp of credit analysis, risk assessment, and financial statement interpretation.
• You understand concepts like PD, LGD, ECL, credit scoring, loan performance drivers, and portfolio segmentation (or you’re excited to learn).
• You can balance quantitative analysis with sound judgment.
• You know how to translate data into clear decisions and actionable recommendations

Technical Skills We Value:

• Experience with credit risk modelling or exposure to risk frameworks
• Strong Excel/Google Sheets & financial modelling
• Understanding of data analysis tools (SQL, Python, Power BI, or willingness to learn)
• Ability to identify risk patterns, emerging trends, and early warning signals
• Familiarity with digital lending, scoring systems, or credit underwriting best practices
• Ability to contribute to improving credit policies, scoring rules, and internal processes.