
Fraud Data Analyst
4 weeks ago
Fraud Analytics
1. Develop Fraud Detection Models: Design and deploy predictive analytics models and machine learning algorithms to identify suspicious activities and patterns.
2. Enhance Systems: Continuously optimize fraud monitoring systems to improve detection accuracy and reduce false positives.
3. Data-Driven Insights: Analyze internal and external data sources to identify vulnerabilities and recommend proactive measures.
4. Performance Metrics: Define and track key performance indicators (KPIs) to measure the effectiveness of fraud detection strategies.
Market Intelligence
1. Industry Monitoring: Stay updated on emerging fraud tactics, industry benchmarks, and regulatory changes.
2. Competitor Analysis: Analyze competitors' risk management strategies to identify opportunities for improvement.
3. Market Trends: Provide actionable insights from market intelligence to inform strategic decision-making.
Team Leadership
1. Build and Lead: Recruit, develop, and mentor a high-performing team of data analysts, data scientists, and market intelligence specialists.
2. Stakeholder Collaboration: Work closely with risk management, compliance, IT, and other departments to ensure alignment and effective communication.
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Qualifications
Education
• Master's degree in data science, Statistics, Economics, Business Administration, or a related field.
Experience
• 10+ years of experience in fraud analytics, risk management, or data analytics
• Proven track record of developing and implementing fraud detection systems.
• Experience with market intelligence tools and competitive analysis.
Technical Skills
• Expertise in data analytics tools (e.g., Python, R, SQL, SAS).
• Familiarity with machine learning platforms and fraud detection software.
• Knowledge of industry-specific regulations and compliance standards.
Key Competencies
• Strong analytical and problem-solving skills.
• Excellent leadership and team-building abilities.
• Strategic thinker with strong business acumen.
• Effective communicator with the ability to convey complex data insights to non-technical stakeholders.
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