The Business Analytics Lead Analyst is part of the Fusion Analytics Team at Citi, focusing on creating analytical solutions to mitigate fraud across various lines of business. This role requires strong expertise in machine learning, predictive modeling, and financial data analysis, with an emphasis on digital fraud detection and cybersecurity. The ideal candidate will collaborate with cross-functional teams to develop data-driven solutions and generate insights for leadership. The position involves analyzing compromised data and leveraging AI/ML models to enhance fraud detection efficiency.

• Bachelor’s degree in engineering, Statistics, Economics, Finance, Mathematics or a related quantitative field from a premier institute required.
• Minimum 5+ relevant experience in data analysis, data mining, or statistical analysis.
• Must have a working knowledge of Python, SQL, Teradata, RDBMS, Hadoop/Hive Tools.
• Experience in statistical analysis with working knowledge of at least one of the following statistical software packages: Python (Preferred), SQL, SAS (required).
• Experience with AI/ML Frameworks (eg TensorFlow, PyTorch, Scikit-learn).
• Knowledge of Large language models (LLM’s) for text analysis and Fraud Intelligence.
• Experience in Predictive modeling, statistical analysis and machine learning techniques.
• Ability to analyze large-scale, unstructured data and generate actionable insights.
• Familiarity with digital fraud detection tools and experience working with cybersecurity datasets and threat intelligence platforms.
• Prior experience in developing dynamic dashboards using visualization tools such as Tableau.

• Create analytical solutions to mitigate losses across all lines of business utilizing various statistical and advanced data science techniques.
• Analyze compromised cards data from the dark web to identify emerging fraud trends and detect suspicious patterns.
• Leverage AI/ML models to anticipate fraudulent behavior.
• Develop and enhance data models and algorithms to identify high-risk accounts for proactive monitoring.
• Collaborate with threat intelligence teams to incorporate external fraud signals into risk models.
• Generate executive-level insights and reports for the leadership team using advanced visualization techniques.
• Lead proof of concepts with new vendors to evaluate fraud detection tools and data enrichment platforms.
• Perform ad-hoc analysis on large, unstructured datasets to identify fraud indicators.
• Manage significant fraud events by coordinating information sharing across financial crime and fraud prevention organizations.
• Collaborate with fraud analytics modeling functions to develop new analytical solutions leveraging unstructured data.

• Citi offers a comprehensive benefits package including competitive pay, stock programs, healthcare coverage, retirement plans, paid time off, parental leave, and programs supporting employee wellbeing and professional development.