Citigroup - Jacksonville, FL

posted 5 months ago

Full-time - Mid Level
Jacksonville, FL
Credit Intermediation and Related Activities

About the position

The Fraud Intelligence Lead Analyst/Data Engineer position is a critical role within the Internal Fraud Intelligence team at Citi. This role is designed for a professional who will lead internal fraud analytics across North America (NAM), engaging and collaborating with various business, fraud, and control stakeholders. The primary focus is to utilize advanced analytics to proactively identify fraud risks and trends, ensuring the integrity and quality of internal fraud detection data. The successful candidate will work closely with technology teams to implement the appropriate analytics platform, data structure, pipeline, and transformation processes within the Citi Bigdata ecosystem. In this role, the analyst will extract knowledge and insights from data to design complex internal fraud detection solutions. This involves employing a range of data preparation, modeling, and visualization techniques, including predictive analysis, pattern recognition, and machine learning. Key skills required for this position include association rule learning, cluster analysis, anomaly detection, and proficiency in data visualization tools such as PowerBI, Qlik, and Tableau, as well as programming languages like Python, Spark, and SAS. The analyst will serve as the regional analytics point person for stakeholder management and communication, which includes participating in regional assurance reviews such as Internal/External Audit reviews and Compliance Assurance reviews. Additionally, the role supports the Internal Fraud Governance team in designing and executing analytical processes, including change management initiatives. The position requires flexibility to attend meetings outside of normal business hours, reflecting the dynamic nature of the work and the need for collaboration across different time zones.

Responsibilities

  • Lead internal fraud analytics in NAM, engaging and collaborating with business, fraud, and control stakeholders.
  • Use advanced analytics to proactively identify fraud risk and trends.
  • Own the knowledge and quality of internal fraud detection data in NAM.
  • Collaborate with technology to implement the right analytics platform, data structure, pipeline, and transformation in Citi Bigdata ecosystem.
  • Extract knowledge and insights from data to design complex internal fraud detection solutions through data preparation, modeling, and visualization techniques.
  • Utilize predictive analysis, pattern recognition, and machine learning techniques.
  • Serve as the regional analytics point person for stakeholder management and communication.
  • Support Internal Fraud Governance team to design and execute analytical processes such as change management.

Requirements

  • Bachelor's Degree required in statistics, mathematics, physics, economics, or other analytical or quantitative discipline; Master's Degree or PhD preferred.
  • 5-8 years of experience in data analytics, modeling, and analytical project implementation.
  • Experience working in a Big Data environment with hands-on coding experience in traditional (SAS, SQL) and/or open source (Python, Impala, Hive) tools.
  • Familiarity with traditional and advanced machine learning techniques and algorithms, such as Logistic Regression, Gradient Boosting, and Random Forests.
  • Proficiency in data visualization tools, such as Tableau.
  • Excellent quantitative and analytic skills; ability to derive patterns, trends, and insights, and perform risk/reward tradeoff analysis.
  • Good written and verbal communication skills, with the ability to connect analytics to business impacts; comfortable presenting to peers and management.
  • Extremely detail-oriented with intellectual curiosity.
  • Ability to provide analytic thought leadership and manage project planning effectively.
  • Creative problem-solving skills and a deep understanding of data management, including data pipeline and data quality.

Nice-to-haves

  • Experience with exploratory analysis.
  • Ability to analyze code to understand its purpose, structure, and design.

Benefits

  • Medical, dental & vision coverage
  • 401(k)
  • Life, accident, and disability insurance
  • Wellness programs
  • Paid time off packages including vacation, sick leave, and paid holidays
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