Associate, Risk Scoring & Decisioning at Flutterwave

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.

We are recruiting to fill the position below:

Job Title: Associate, Risk Scoring & Decisioning

Location: Lekki, Lagos
Category: Risk Organisation

The Role

• We are seeking highly skilled and experienced We are seeking an ambitious & experienced Associate, Risk Scoring and Decisioning 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.
• This position requires a deep understanding of risk assessment methodologies, 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 scoring models, optimizing decisioning systems, and contributing to overall risk management frameworks.

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.

Required Competency and Skillset to be a Waver

• Bachelor's Degree in a quantitative field such as Mathematics, Statistics, Computer Science, Economics, or related discipline; advanced degree preferred.
• Minimum of 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.

Application Closing Date
Not Specified.

How to Apply
Interested and qualified candidates should:
Click here to apply online