Senior Manager Fraud & Scams Analytics

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Role Overview

Senior Manager Fraud & Scams Analytics

This role demands strong analytical leadership, advanced modeling expertise, and the ability to influence senior stakeholders. You will collaborate closely with business leaders, technology teams, and analytics professionals to deliver data-driven insights that shape fraud prevention strategies at scale.

Key Responsibilities

• Partner with senior leadership and key stakeholders to identify business challenges and opportunities that can be addressed through advanced fraud and scam analytics.
  
• Translate complex analytical outputs into clear, actionable insights for non-technical stakeholders and executive audiences.
  
• Lead and manage a team of analytics professionals, providing guidance, mentoring, and performance support to ensure timely delivery of high-quality outcomes.
  
• Oversee the design, development, and deployment of fraud detection models, machine learning algorithms, and advanced analytical solutions.
  
• Challenge analytical assumptions and approaches, ensuring rigor in hypothesis testing, feature selection, and model development.
  
• Collaborate with peer leaders to prioritize analytics features, customer profiles, and data assets aligned with business objectives.
  
• Track team deliverables, manage dependencies, and maintain accurate progress updates using JIRA and related tools.
  
• Ensure robust data governance practices, maintaining high standards of data quality, integrity, security, and regulatory compliance.
  
• Promote best practices in analytics, model governance, and lifecycle management across the organization.
  

Leadership & Team Management

• Lead, mentor, and develop a high-performing team of fraud analytics professionals.
  
• Set clear goals, expectations, and development plans aligned with business priorities.
  
• Foster a collaborative, innovative, and accountable team culture.
  

Required Skills & Experience

• 9–12 years of experience in

  Data Analytics

  , with significant exposure to fraud, risk, or financial crime analytics.
• Strong expertise in

  fraud detection, scam prevention, transaction monitoring, or financial risk analytics

  .
• Proven experience building and supervising

  advanced analytical models and machine learning solutions

  .
• Hands-on proficiency in

  Python and/or SQL

  , with the ability to mentor and upskill team members.
• Strong stakeholder management skills, with the ability to translate analytical problems and insights across technical and non-technical audiences.
  
• Experience working in large-scale, high-volume data environments.
  
• Solid understanding of

  data governance, regulatory compliance, and data security standards

  .
• Familiarity with

  data engineering concepts

  and modern analytics platforms is an advantage.

Educational Qualifications

• Bachelor’s or Master’s degree in

  Computer Science, Engineering, Information Technology

  , or a numerate discipline such as

  Actuarial Science, Applied Mathematics, Statistics, Data Science, or Computing Science

  .

Why Join Us

• Work on industry-leading fraud and scam prevention platforms operating at massive scale.
  
• Influence strategic decision-making and enterprise-level fraud prevention initiatives.
  
• Collaborate with senior leaders and cross-functional experts in a high-impact environment.
  
• Be part of a diverse, inclusive, and analytics-driven culture focused on protecting customers and building trust.