Flutterwave was founded on the principle that every African must be able to participate and thrive in the global economy. To achieve this objective, we have built a trusted payment infrastructure that allows consumers and businesses (African and International) make and receive payments in a convenient border-less manner.
Flutterwave is seeking ambitious & experienced Risk Modeling and Decisioning professionals to join our dynamic team. The successful candidate will play a critical role in enhancing our risk management strategies and ensuring the integrity of our decision-making processes using predictive analytics.
This position requires a deep understanding of risk/fraud modeling methodologies, advanced data analytic techniques, statistical analysis, and data-driven decision-making within the fintech industry.
The ideal candidate will have a proven track record of developing and implementing risk/fraud/compliance models, designing processes, optimizing decisioning systems, and contributing to overall risk management frameworks.
Responsibilities
Assist in developing and refining analytic models/processes and strategies to assess credit/fraud/compliance 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 and strategies into our decisioning systems.
Monitor the performance of risk 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.
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 models, methodologies, and decisioning processes.
Participate in audits and regulatory examinations, ensuring compliance with relevant laws and regulations.
Requirements
Bachelor's Degree in a quantitative field such as Mathematics, Statistics, Computer Science, Economics, or related discipline; advanced degree preferred.
2+ years of experience in risk management, analytic modeling, ML modeling, credit/fraud scoring, or related fields within the financial services industry.
Strong technical skills including proficiency in Python and statistical analysis and programming languages like SQL.
Experience with machine learning techniques and tools for building predictive models (e.g., logistic regression, decision trees, random forests, gradient boosting and neural network).
Critical thinking & problem solving skills – ability to assess situations, verify facts, reason logically to come up with options and propose sound recommendations.
Familiarity with risk management frameworks, methodologies, and regulatory requirements (e.g. GDPR).
Experience developing and implementing analytical models, preferably in a fintech or lending environment.
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.