Description

You will develop and deploy machine learning models and statistical methods to detect and prevent fraudulent activities.

This role is hybrid.

Responsibilities

• Develop and deploy machine learning models to detect, predict, and prevent fraudulent transactions and behavior patterns.
• Analyze large volumes of structured and unstructured data to identify fraud trends and root causes.
• Collaborate with fraud operations, engineering, and compliance teams to implement real-time detection solutions.
• Design and monitor KPIs to evaluate model performance and improve fraud detection systems.
• Conduct deep-dive investigations into fraud cases to create actionable insights and detailed reports.

Required Skills

• 10+ years of professional experience in data science.
• Proficiency in Python, SQL, and SAS.
• Experience with supervised and unsupervised fraud detection, anomaly detection, behavioral modeling, and network analysis.
• Experience working with large datasets and cloud platforms such as AWS, GCP, or Azure.
• Experience in the responsible use of AI in solution design.
• Proficiency with visualization tools including Tableau and Power BI.
• Bachelor’s or master’s degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related field.

Preferred Skills

• Experience with real-time fraud detection systems.

Key Skills

Education

Any Graduate