Fraud Analytics Lead — ML & Feature Engineering

Citigroup Inc.; Jacksonville (FL); On-site; USD 126,000 - 188,000; Full time

Job summary

Citi in Jacksonville, FL is seeking a senior data scientist to advance fraud prevention through advanced machine learning and feature engineering. You will transform large datasets into robust inputs for fraud models targeting application fraud, synthetic ID, and account takeover.

Collaborate with technology and analytics teams to optimize models, deploy in production, and monitor performance. The role requires strong data processing, EDA, and the ability to translate complex results for

Qualifications

• Bachelor’s degree in statistics, mathematics, physics, economics, or other analytical field.
• 5+ years in data science, machine learning, or advanced analytics.
• Experience with Generative AI and LLM preferred.
• Proficiency in SAS, Python, R, or SQL for data manipulation, feature engineering, and model development.
• Strong experience with data processing tools and libraries (Pandas, NumPy, PySpark) for large datasets.
• Deep understanding of ML algorithms and statistical modeling techniques for fraud detection.
• Expertise in feature engineering, including creating, selecting, and refining features.
• Data engineering: building and optimizing data pipelines, ETL processes, real-time data streaming for fraud detection.
• ML Ops: model development, monitoring, and versioning in production.
• Analytics: ability to conduct EDA and derive actionable insights.
• Collaboration: cross-functional work with tech, analytics, and business teams.
• Communication: translate complex findings for non-technical stakeholders.
• Problem-Solving: analytical and creative thinking in fast-paced environments.
• Regulatory Compliance: familiarity with fraud modeling regulations and best practices.
• Multi-Tasking: manage multiple projects with tight deadlines.
• Attention to Detail: precision in data analysis and reporting.
• Intellectual Curiosity: stay updated with latest fraud detection techniques.

Responsibilities

• Lead data and feature engineering to extract high-quality inputs for fraud models.
• Build predictive models and AI algorithms on large structured and unstructured data.
• Design and implement ML models across the lifecycle including application, synthetic ID, and account takeover fraud.
• Develop advanced data processing techniques for large, complex datasets.
• Conduct exploratory data analysis to uncover patterns for model development.
• Collaborate with tech teams, analytics, and business partners to align data strategies.
• Continuously optimize models via feature selection and hyperparameter tuning.
• Support production deployment and real-time fraud detection with feedback loops.
• Evaluate and select ML algorithms based on data characteristics.
• Participate in model validation and compliance with regulatory standards.
• Generate and manage regular and ad-hoc fraud monitoring reports.

Skills

Data science

Machine learning

Generative AI

Python

SQL

Pandas

NumPy

EDA

Communication

Collaboration

Problem solving

Education

Bachelor's degree

Master's degree

Tools

SAS

Python

R

SQL

SAS/ETL

Job description

Citi in Jacksonville, FL is seeking a senior data scientist to advance fraud prevention through advanced machine learning and feature engineering. You will transform large datasets into robust inputs for fraud models targeting application fraud, synthetic ID, and account takeover.

Collaborate with technology and analytics teams to optimize models, deploy in production, and monitor performance. The role requires strong data processing, EDA, and the ability to translate complex results for