Fraud Data Analyst: Risk Insights & Dashboards

Moniepoint Group; United States; Teletrabalho; USD 90 000 - 130 000; Tempo integral

Resumo da oferta

Moniepoint is seeking a Data Analyst (Fraud) to investigate attacks, quantify impact, and present findings. You will build dashboards, propose rule-based mitigations with fraud ops and engineering, and collaborate with data scientists, engineers, and product managers to translate insights into action.

The role requires 4+ years in data analysis (fraud/risk), expert SQL, BI tool experience (PowerBI/Looker/Tableau/Superset/Redash), and proficiency with Excel/Google Sheets.

Qualificações

• 4+ years as a Data Analyst (Fraud) or similar role.
• Advanced proficiency with SQL for complex queries on large datasets.
• Experience in fraud, risk, or financial services.
• Proficiency with BI tools (PowerBI, Looker, Tableau, Superset, or Redash).
• Proficiency with spreadsheet tools (Excel or Google Sheets).
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
• Strong problem-solving and stakeholder management skills.
• Exposure to Python or scripting for data manipulation.

Responsabilidades

• Investigate fraud attacks, quantify their impact, and present clear findings.
• Propose and refine rule-based mitigations in collaboration with fraud operations and engineering.
• Build and maintain reporting and dashboards to monitor fraud trends and operational metrics.
• Work closely with data scientists, engineers, and product managers to translate insights into action.
• Proactively identify emerging patterns and flag risks before they elevate.

Conhecimentos

Problem solving

Stakeholder management

Attention to detail

Fraud domain knowledge

Formação académica

Bachelor’s degree in CS/Statistics/Math/Engineering

Ferramentas

PowerBI

Looker

Tableau

Superset

Redash

Excel

Google Sheets

Descrição da oferta de emprego

Moniepoint is seeking a Data Analyst (Fraud) to investigate attacks, quantify impact, and present findings. You will build dashboards, propose rule-based mitigations with fraud ops and engineering, and collaborate with data scientists, engineers, and product managers to translate insights into action.

The role requires 4+ years in data analysis (fraud/risk), expert SQL, BI tool experience (PowerBI/Looker/Tableau/Superset/Redash), and proficiency with Excel/Google Sheets.