Chief Data Fraud Prevention Specialist

5 days ago


Mount Abu, Rajasthan, India beBeeInvestigator Full time ₹ 18,00,000 - ₹ 24,00,000
Lead Investigative Data Analyst

The role of the Lead Investigative Data Analyst is crucial to our organization's effectiveness, contributing significantly to the development of investigative tools and technologies, data processes, and reporting.

Key Responsibilities:
  • Develop and maintain the effectiveness of investigation tools and technologies, data processes, and reporting.
  • Support data analysts and modeling experts in the Investigation & Loss Mitigation team.
Principal Accountabilities:
  1. Deliver actionable business insights through advanced data analysis and modeling.
  2. Identify valuable data sources and automate collection processes.
  3. Analyze large datasets to discover trends and patterns, utilizing machine learning algorithms and ensemble modeling techniques.
  4. Present complex information using effective data visualization techniques.
  5. Collaborate with cross-functional teams to develop strategic initiatives and optimize data management practices.
  6. Formulate policies for effective data management and enforce them across the organization.
System Validations:
  • Monitor emerging fraud trends, investigate threats, and rapidly develop and deploy new strategies to manage those threats.
  • Build predictive models and machine-learning algorithms to identify potential risks.
  • Optimize database systems and analyze information and data systems to enhance their performance.
  • Review existing control environments and assess their effectiveness against known fraud schemes, identifying control gaps and creating insightful analyses to support new controls.
People Management:
  • Work collaboratively with a diverse team of operational agents, fraud risk managers, data analysts/scientists, business insight analysts, and subject matter experts.
  • Develop and maintain data models, reporting systems, data automation systems, dashboards, and performance metrics to support key decisions.
Educational Qualifications:
  • Master's degree in Statistics, Economics, or Engineering, or Professional education in Data Science.
  • Advanced knowledge of Python, R, SQL, MS Excel, and SQL databases and coding.
  • Bachelor's degree in Mathematics, Computer Science, Engineering, Economics, or Statistics.


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