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Job Description
Assist in developing and refining risk scoring models to assess credit risk, fraud risk, and other relevant risks associated with our products and services.
Responsibilities
- Assist in developing and refining risk scoring models to assess credit risk, fraud risk, and other relevant risks associated with our products and services.
- Conduct comprehensive analysis of historical data and market trends to identify patterns and insights that inform risk management strategies.
- Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to implement risk scoring models into our decisioning systems.
- Monitor the performance of risk scoring models and decisioning systems, identifying opportunities for improvement and optimization.
- Stay abreast of industry best practices, regulatory requirements, and emerging trends in risk management and decision sciences.
- Build timely and error-free reports and dashboards for various Risk metrics
- Carry out analytics activities at all stages of data analytics life-cycle – understanding business needs, explore and examine data from multiple sources, help build workflows for extraction and cleaning of data, conduct exploratory data analysis
- Provide analytical support and insights to senior management and stakeholders to aid in strategic decision-making processes.
- Develop and maintain documentation related to risk scoring models, methodologies, and decisioning processes.
- Participate in audits and regulatory examinations, ensuring compliance with relevant laws and regulations.
Qualification
- Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Computer Science, Economics, or related discipline; advanced degree preferred.
- Minimum 4+ years of experience in risk management, credit scoring, or related fields within the financial services industry.
- Hands-on experience on PowerBI, DAX, Python, and SQL.
- Critical thinking & problem solving skills – ability to assess situations, verify facts, reason logically to come up with options and propose sound recommendations.
- Experience with machine learning techniques and tools for building predictive models (e.g., logistic regression, decision trees, random forests, gradient boosting).
- Familiarity with risk management frameworks, methodologies, and regulatory requirements (e.g. GDPR).
- Experience developing and implementing risk scoring models, preferably in a fintech or lending environment.
- Knowledge of machine learning techniques and their application to risk management is a plus.
- Excellent analytical skills with the ability to translate complex data into actionable insights.
- Strong communication and collaboration skills with the ability to work effectively in cross-functional teams.
- Detail-oriented with a focus on accuracy and quality of work.
- Familiarity with regulatory requirements and compliance standards in the financial services industry.
Location: Nigeria.
Apply: ASSOCIATE RISK SCORING AND DECISIONING
