Head of Fraud Data Analytics

The core responsibilities for the job include the following:
Fraud Analytics:
Develop Fraud Detection Models: Design and deploy predictive analytics models and machine learning algorithms to identify suspicious activities and patterns.
Enhance Systems: Continuously optimise fraud monitoring systems to improve detection accuracy and reduce false positives.
Data-Driven Insights: Analyse internal and external data sources to identify vulnerabilities and recommend proactive measures.
Performance Metrics: Define and track key performance indicators (KPIs) to measure the effectiveness of fraud detection strategies.
Market Intelligence:
Industry Monitoring: Stay updated on emerging fraud tactics, industry benchmarks, and regulatory changes.
Competitor Analysis: Analyse competitors' risk management strategies to identify opportunities for improvement.
Market Trends: Provide actionable insights from market intelligence to inform strategic decision-making.
Team Leadership:
Build and Lead: Recruit, develop, and mentor a high-performing team of data analysts, data scientists, and market intelligence specialists.
Stakeholder Collaboration: Work closely with risk management, compliance, IT, and other departments to ensure alignment and effective communication.
Requirements:
Master's degree in Data Science, Statistics, Economics, Business Administration, or a related field.
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, and 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.

Experience
8-12 yrs