Description

You lead end-to-end scientific strategy for large-scale fraud and risk modeling initiatives. This role is on-site.

Responsibilities

• Define problem statements, success metrics, and long-term modeling roadmaps in partnership with business and engineering leaders.
• Design, develop, and deploy highly scalable machine learning systems in real-time production environments.
• Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies to automate and transform risk evaluation.
• Establish best practices for experimentation, model validation, monitoring, and lifecycle management.
• Mentor junior scientists through technical guidance and raise the team's technical bar.

Required Skills

• 5+ years of experience in Data Science, Statistical Modeling, and Machine Learning.
• Strong proficiency in Python for data science and model development.
• Hands-on experience with Deep Learning and Generative AI frameworks.
• Proven track record in Fraud Detection and Risk Management.
• Experience with MLOps and deploying models to production.
• Ability to communicate complex scientific insights to senior leadership.
• Experience with Large Language Models (LLMs).

Preferred Skills

• Experience with terabyte-scale data processing and real-time production systems.
• Background in system architecture design and experimentation frameworks.
• Experience in eCommerce or financial services environments.

Key Skills

Education

Any Graduate