Description

Design, develop, and deploy scalable machine learning models for fraud detection and predictive analytics.

This role is on-site.

Responsibilities

• Develop and evaluate predictive models to prevent fraud, theft, and abuse.
• Extract insights from large-scale historical business data to automate key processes.
• Collaborate with engineering teams to implement real-time model deployments and new features.
• Lead projects and mentor scientists and engineers in machine learning best practices.
• Establish automated pipelines for data analysis, model development, and validation.

Required Skills

• 10+ years of experience in Data Science and Machine Learning.
• Strong proficiency in Python for statistical analysis and algorithm development.
• Experience with MLOps, including model deployment and monitoring.
• Expertise in predictive modeling, data mining, and statistical techniques.
• Ability to design scalable solutions for complex business problems.

Preferred Skills

• Experience with large-scale data processing and real-time model deployment.
• Background in fraud detection systems or financial transaction analysis.

Key Skills

Education

Any Graduate