Senior Fraud Analytics Data Scientist

Citi; New York (NY); Hybrid; USD 97,000 - 145,000; Full time

Benefits offered by this job

Medical, dental & vision coverage

401(k) retirement plan

Life, disability insurance

Paid time off

Job summary

Citi is seeking a Specialized Analytics Senior Analyst in a hybrid role. You will lead data and feature engineering for fraud models, build predictive ML solutions, and collaborate with technology, analytics, and business teams to enhance real-time fraud detection across the lifecycle.

The ideal candidate has strong Python/SQL skills, experience with Pandas, PySpark, and ML algorithms, and a focus on regulatory compliance and model governance.

Qualifications

• Bachelor’s degree in statistics, mathematics, economics, or other quantitative discipline.
• 3+ years in data science, machine learning, or advanced analytics.

Responsibilities

• Lead data and feature engineering to prepare inputs for fraud model development.
• Build predictive models and ML algorithms with large structured and unstructured data.
• Design and implement advanced ML models for fraud detection across lifecycle stages.
• Perform data processing, cleaning, normalization, and augmentation for robust model performance.
• Conduct Exploratory Data Analysis to uncover patterns informing modeling.
• Collaborate with tech, analytics, and business partners to align data strategies.
• Optimize models through feature selection and hyperparameter tuning for adaptability.
• Support deployment of models into production for real-time fraud detection.
• Evaluate ML algorithms and tools based on fraud detection needs and data characteristics.
• Participate in data quality and governance initiatives to enhance prevention capabilities.
• Contribute to model validation and regulatory-compliant practices.

Skills

Python

R

SQL

Pandas

PySpark

ML algorithms

Feature engineering

Fraud detection

Data pipelines

EDA

Education

Bachelor’s degree

Master’s degree preferred

PhD preferred

Job description

Citi is seeking a Specialized Analytics Senior Analyst in a hybrid role. You will lead data and feature engineering for fraud models, build predictive ML solutions, and collaborate with technology, analytics, and business teams to enhance real-time fraud detection across the lifecycle.

The ideal candidate has strong Python/SQL skills, experience with Pandas, PySpark, and ML algorithms, and a focus on regulatory compliance and model governance.