Data Analyst - Fraud

About Moniepoint

Moniepoint is a comprehensive financial services platform focused on emerging markets and stands as the second-fastest growing company in Africa. Since 2019, it has supported over three million users with personal and business banking, payments, credit, and business management solutions. In 2023, Moniepoint processed transactions totaling $182 billion, handling the majority of point-of-sale (POS) operations in Nigeria.

Role Overview

As a Data Analyst specializing in fraud, you will investigate and quantify the impact of fraud incidents, presenting findings to support prioritization and response. You will develop and refine rule-based fraud mitigation strategies, collaborating with operations and engineering teams to implement solutions. Managing dashboards and reports to track fraud patterns, rule effectiveness, and key operational metrics will be integral to your role. You will work closely with cross-functional teams, including fraud operations, data science, engineering, and product management, to ensure analytical insights inform actionable decisions. Proactively identifying emerging fraud tactics and risks is also expected.

Key Responsibilities

• Analyze and assess fraud attacks, measuring their impact and delivering clear reports to guide responses.
• Design and improve rule-based controls in partnership with relevant teams to prevent fraud.
• Create and maintain dashboards that monitor fraud trends, performance of fraud rules, and operational KPIs.
• Collaborate effectively with diverse teams to translate data analysis into practical fraud prevention measures.
• Detect and report new fraud activity patterns before they escalate.

Candidate Requirements

• Demonstrable experience as a Data Analyst in fraud or a related field, with at least 4 years of relevant work or equivalent achievements.
• Strong analytical and problem-solving capabilities.
• Advanced SQL skills for complex queries across large datasets.
• Background in fraud, risk management, or financial services with a solid understanding of fraud methodologies and mitigation techniques.
• A proactive approach to identifying unusual data and investigating anomalies.
• Familiarity with Python or other scripting languages for data processing and analysis.
• Competency in at least one business intelligence tool (e.g., PowerBI, Looker, Tableau, Superset, Redash).
• Excellent stakeholder management, with the ability to convey insights clearly to various audiences including leadership.
• Experience working in dynamic, cross-functional teams where priorities can shift rapidly.
• Proficient with spreadsheet software such as Microsoft Excel or Google Sheets.
• Comfortable operating in a flat organizational structure with significant autonomy.
• Strong written and verbal communication skills.
• Commitment to continual learning and mastery of new data technologies and methodologies.
• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or related discipline.

Desirable Additional Skills

• Experience with data governance practices.
• Additional proficiency in Python or similar scripting languages.
• Familiarity with version control systems like Git.

What Moniepoint Offers

• A culture that prioritizes employee well-being, values diverse opinions, and fosters mutual respect and support.
• An environment focused on continuous learning and professional development through training and knowledge sharing.
• Competitive compensation including salary, pension, health insurance, annual bonuses, and other benefits.

Hiring Process

• Initial phone screening with a recruiter.
• Technical assessment involving a SQL test to evaluate skills.
• Technical interview with the hiring manager.
• Behavioral interview with the Head of Data Analytics/Science and Fraud Team.

Diversity and Inclusion

Moniepoint is an equal opportunity employer committed to fostering a diverse and inclusive workplace for all employees and applicants.