AVP- Fraud Analytics(Strategy)

About The Role The AIM Financial Crime and Fraud Prevention Analytics team is seeking a Data Science–driven Senior Analyst to lead the re-imagining of fraud strategy design, development, and deployment using advanced AI and automation-led approaches. This role is central to accelerating speed-to-market for fraud strategies, reducing manual effort, and enabling scalable, adaptive decisioning across products and channels.

This position applies machine learning, advanced analytics, and AI-enabled tooling to modernize how fraud strategies are conceptualized, tested, governed, and deployed. Rather than owning full regulatory model development, the role focuses on embedding intelligence, automation, and experimentation into the fraud strategy lifecycle, partnering closely with Fraud Strategy leadership, Technology, Data Engineering, and Modeling teams.

This is a senior individual contributor (C12) role with a mandate to drive strategic change, influence design standards, and shape the future operating model for fraud strategy execution.

Role Objective The objective of this role is to transform the fraud strategy operating model by leveraging AI and data science to:

• Reduce cycle time from insight to production
• Enable rapid experimentation and iteration of fraud strategies
• Shift strategy development from manual, rule-heavy processes to AI-augmented decisioning
• Improve scalability, consistency, and governance of fraud strategy execution

Key Responsibilities Fraud Strategy Transformation & AI Enablement

• Lead initiatives to redesign the end-to-end fraud strategy lifecycle using AI-driven analysis and automation
• Identify opportunities to augment or replace manual processes with machine learning and advanced analytics
• Define frameworks for rapid strategy prototyping, testing, and deployment
• Drive adoption of reusable analytical components and modular strategy design

Applied Data Science & Advanced Analytics

• Apply machine learning and statistical techniques such as logistic regression, gradient boosting, random forests, clustering, and anomaly detection
• Perform large-scale exploratory and confirmatory data analysis on transactional and behavioral datasets
• Support feature discovery, signal evaluation, and strategy optimization
• Use explainability techniques to translate analytical outputs into actionable strategy insights

Speed-to-Market & Experimentation

• Champion fast-cycle experimentation including A/B testing and challenger strategies
• Develop performance measurement frameworks balancing fraud loss, customer friction, and efficiency
• Partner with Technology and Data Engineering teams to ensure scalable production deployment

Strategic Partnership & Influence

• Act as a thought partner to Fraud Strategy leadership, framing insights in business terms
• Collaborate with Fraud Modeling teams by contributing feature insights and challenger concepts
• Prepare senior-level communications outlining strategy transformation outcomes and roadmaps

Governance, Risk & Conduct

• Ensure AI-enabled strategies comply with internal policy, regulatory, and ethical standards
• Apply sound judgment and escalate control issues transparently

Qualifications Experience

• 6–10 years of experience in analytics, data science, fraud, risk, or decision science

Core Data Science & AI Skills

• Strong hands-on experience with Python for data analysis and machine learning
• Solid understanding of ML algorithms including logistic regression, tree-based models, and gradient boosting
• Experience with model evaluation metrics such as ROC, precision-recall, and stability measures
• Ability to work with large datasets using SQL, Hive, Spark, or PySpark

Strategy & Business Skills

• Strong analytical judgment with the ability to translate techniques into deployable strategy solutions
• Proven ability to influence stakeholders using data-driven insights

Ways of Working

• Self-starter with strong ownership mindset and bias for action
• Comfortable operating across Strategy, Technology, and Modeling teams
• Strong communication and storytelling skills

Education

• Bachelor’s or Master’s degree in a quantitative field or equivalent practical experience

This role focuses on AI-enabled fraud strategy transformation and speed-to-market and does not carry end-to-end ownership of regulatory model development or independent model validation.

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Job Family Group: Decision Management

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Job Family: Specialized Analytics (Data Science/Computational Statistics)

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Time Type: Full time

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Most Relevant Skills Please see the requirements listed above.

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Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.

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