Head of Core Insights, Data Science

Position Overview

The Head of Core Insights, Data Science is a senior leadership role responsible for driving research, analytics, and data science initiatives focused on fraud, identity risk, financial crime, and related adversarial ecosystems. This individual will lead the development of rigorous, market-facing research and actionable intelligence that informs strategic decision-making, supports product innovation, and enhances organizational thought leadership.

The ideal candidate combines deep quantitative expertise with extensive domain knowledge in fraud and identity risk. They possess a strong foundation in causal inference, econometrics, machine learning, and large-scale data analytics, along with the ability to translate complex findings into clear insights for executive, regulatory, and industry audiences..

Key Responsibilities

Research & Advanced Analytics

• Lead the design and execution of advanced research initiatives focused on fraud, identity risk, financial crime, and emerging threat patterns.
• Apply rigorous quantitative methodologies to evaluate trends, behaviors, and risk signals within large-scale identity, behavioral, and transaction datasets.
• Develop and oversee causal inference frameworks to distinguish correlation from causation and generate actionable business insights.
• Conduct analyses utilizing econometric, statistical, machine learning, and network-based methodologies.
• Identify emerging fraud typologies, attack vectors, and evolving adversarial behaviors to inform organizational strategy.

Data Science Leadership

• Build, lead, and develop high-performing teams of data scientists, researchers, economists, and analytics professionals.
• Establish best practices for statistical modeling, experimentation, causal analysis, and model governance.
• Guide the development of scalable analytical frameworks and data products that support operational and strategic objectives.
• Partner with engineering, product, risk, and business stakeholders to operationalize insights and research findings.

Fraud & Identity Intelligence

• Serve as a subject matter expert on fraud prevention, identity verification, financial crime, and related risk domains.
• Analyze fraud ecosystems, identity networks, synthetic identities, account takeover activity, mule networks, and other complex fraud patterns.
• Evaluate how regulatory, technological, and market changes impact fraud incentives, risk exposure, and consumer behavior.
• Leverage graph analytics and network modeling techniques to uncover relationships and identify emerging threats.

Thought Leadership & Industry Engagement

• Represent the organization as a trusted industry voice through conferences, publications, research reports, and professional forums.
• Author and oversee the development of high-impact research, white papers, and market-facing insights.
• Engage with regulators, industry groups, and external stakeholders on topics related to fraud, identity risk, and financial crime.
• Build credibility and influence through data-driven research and evidence-based recommendations.

Executive Communication

• Present complex analytical findings to executive leadership, board members, regulators, and external audiences.
• Translate sophisticated quantitative research into clear, concise, and actionable insights without sacrificing rigor or nuance.
• Develop executive briefings, strategic reports, and recommendations that support business and policy decisions.



Qualifications

Required

• Advanced degree (Master’s or PhD preferred) in Economics, Statistics, Econometrics, Applied Mathematics, Computer Science, Data Science, or a related quantitative field.
• 10+ years of experience in data science, fraud analytics, quantitative research, risk management, econometrics, or related disciplines.
• Demonstrated expertise in fraud, identity risk, financial crime, or other adversarial risk environments.
• Strong command of causal inference methodologies, statistical modeling, econometrics, and machine learning techniques.
• Experience working with large-scale transactional, behavioral, identity, or network datasets.
• Proficiency in Python, SQL, and modern analytical and machine learning tools.
• Proven experience leading and developing high-performing technical teams.
• Exceptional written and verbal communication skills with the ability to influence diverse audiences.
• Demonstrated track record of external thought leadership through publications, conference presentations, industry engagement, or similar activities.

Preferred

• Experience with graph analytics, network modeling, fraud ring detection, and graph databases.
• Familiarity with regulatory frameworks related to identity verification, fraud prevention, financial crime compliance, and consumer protection.
• Experience analyzing device intelligence, behavioral biometrics, digital identity signals, browser fingerprinting, or related fraud indicators.
• Published research in academic journals, industry publications, or recognized market forums.
• Experience within financial services, fintech, payments, credit risk, fraud prevention, or related sectors.
• Knowledge of explainable AI, model governance, and responsible AI frameworks.
• Experience supporting consumer-facing decision systems and risk-based decisioning environments.