Data Analyst - Fraud

About Moniepoint

Moniepoint is a comprehensive financial services platform catering to emerging markets and is recognized as the second-fastest growing company in Africa. Since 2019, it has empowered over 3 million individuals with personal and business banking, payment solutions, credit, and business management tools. In 2023, Moniepoint processed $182 billion and handles most point-of-sale transactions across Nigeria.

Key Responsibilities

• Analyze and investigate instances of fraud to assess their impact and produce detailed reports that guide prioritization and response strategies.
• Develop and enhance rule-based fraud mitigation approaches, collaborating with fraud operations and engineering teams through to deployment.
• Create and maintain dashboards and reports to track trends in fraud, assess rule effectiveness, and monitor important operational metrics.
• Coordinate with fraud operations, data scientists, engineers, and product managers to ensure that insights derived from data lead to actionable outcomes.
• Detect emerging fraud patterns proactively and alert stakeholders to potential risks before they escalate.

Candidate Requirements

• Demonstrated experience as a Data Analyst specializing in fraud detection or a similar role with at least 4 years of relevant work history or equivalent achievements.
• Strong analytical and problem-solving skills to dissect complex data and situations.
• Exceptional SQL skills, capable of building complex queries to analyze and segment large datasets.
• Background in fraud, risk management, or financial services with a solid understanding of how fraud operates and how to balance mitigation options.
• A proactive and investigative approach to work, taking initiative without prompting.
• Familiarity with Python or scripting languages used for data manipulation and analysis.
• Competence with BI tools such as PowerBI, Looker, Tableau, Superset, or Redash.
• Excellent interpersonal skills enabling clear communication of findings to diverse groups including fraud operations, product teams, engineers, and senior leaders, and the ability to influence decision-making using data.
• Experience working in dynamic, cross-disciplinary environments with shifting priorities.
• Proficiency with spreadsheet applications like Microsoft Excel or Google Sheets.
• Ability to operate autonomously within a flat organizational structure, affecting significant impact across millions of customers.
• Strong verbal and written communication abilities.
• A commitment to continuously learning and adopting new technologies and analytical methods.
• A bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related discipline.

Desirable Skills

• Knowledge of data governance principles.
• Experience with version control systems such as Git.

Benefits and Culture

• A people-first environment that emphasizes employee wellbeing and values diverse voices and mutual respect.
• An organizational culture focused on continuous learning, knowledge sharing, training, and regular internal technical sessions.
• Competitive compensation including salary, pension, health insurance, annual bonuses, and additional benefits.

Hiring Process

• Initial phone screening with a recruiter.
• A technical take-home SQL test.
• Technical interview with the hiring manager.
• Behavioral interview sessions with the Head of Data Analytics/Science and Fraud Team.

Equal Opportunity Employer

Moniepoint is committed to diversity and inclusion, ensuring an equitable workplace for all employees and candidates.