This role is part of Citi's Financial Crimes and Fraud Prevention team, focusing on leveraging advanced machine learning tools and data mining techniques to combat fraud. The primary responsibilities include data and feature engineering, transforming complex datasets into optimized inputs for fraud models. The ideal candidate will have a strong technical background in data processing and feature engineering, enabling the development of effective fraud detection models. Collaboration with technology teams and business partners is essential to stay informed about fraud risks and optimize prevention strategies.

• Bachelor’s Degree in statistics, mathematics, physics, economics, or other analytical or quantitative discipline; Master's Degree or PhD preferred.
• 3+ years of experience in data science, machine learning, or advanced analytics.
• Proficiency in programming languages such as Python, R, or SQL for data manipulation and model development.
• Strong experience with data processing tools and libraries such as Pandas, Numpy, and PySpark.
• Deep understanding of machine learning algorithms and statistical modeling techniques used for fraud detection.
• Experience with building and optimizing data pipelines and real-time data streaming for fraud detection solutions.
• Familiarity with model development, monitoring, and versioning in production environments.
• Strong ability to conduct exploratory data analysis and identify actionable insights from large datasets.
• Proven track record of working cross-functionally with technology, analytics, and business teams.
• Ability to translate complex technical findings into clear insights for non-technical stakeholders.
• Strong problem-solving skills and ability to think critically in a fast-paced environment.
• Familiarity with regulatory requirements and best practices related to fraud modeling.
• Demonstrated ability to manage multiple projects and priorities while meeting deadlines.
• High level of attention to detail in data analysis and model development.
• Strong intellectual curiosity and eagerness to stay updated with developments in data science and fraud detection.

• Lead data and feature engineering efforts to prepare high-quality data inputs for fraud model development.
• Build predictive models and machine-learning algorithms with structured and unstructured data.
• Design, develop, and implement advanced machine learning models to detect and prevent fraud.
• Utilize advanced data processing techniques to manage large, complex datasets.
• Conduct comprehensive exploratory data analysis to uncover hidden patterns and trends.
• Collaborate closely with technology teams and business partners to align on data strategies.
• Continuously optimize and refine fraud models through feature selection and performance monitoring.
• Support model deployment and integration into production systems for real-time fraud detection.
• Evaluate and select appropriate machine learning algorithms based on fraud detection needs.
• Engage in cross-functional initiatives to enhance data quality and governance.
• Participate in model validation and testing processes to ensure compliance with regulatory standards.
• Generate and manage regular and ad-hoc reporting to monitor and identify emerging trends.

• 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.