Description

Build risk models and predictive analytics to identify insider threats and support governance.

This role is on-site.

Responsibilities

• Design and refine quantitative models, statistical methods, and machine learning algorithms for insider risk detection.
• Collaborate with Cybersecurity, HR, Legal, and Compliance teams to develop analytical frameworks.
• Translate complex enterprise data into clear risk signals and executive-level metrics.
• Develop human risk scores and other predictive tools to enhance detection capabilities.
• Ensure model explainability, governance, and validation meet regulatory standards.

Required Skills

• 5+ years of experience in data science, risk modeling, or quantitative analysis.
• Proficiency in Python and/or R for statistical modeling and analysis.
• Strong SQL skills for large-scale data extraction and manipulation.
• Hands-on experience building regression, classification, anomaly detection, and clustering models.
• Bachelor’s or Master’s degree in Data Science, Statistics, Applied Mathematics, Economics, Quantitative Finance, Computer Science, or related field.
• Ability to explain complex analytical concepts to non-technical stakeholders.
• Experience in regulated industries is preferred.

Key Skills

Education

Any Graduate