Vice President- Applied AI/ML Scientist

Hiring: Vice President - Applied AI/ML Scientist - Fraud & Risk Analytics

Are you passionate about building AI systems that make real-time decisions on live financial transactions Do you thrive at the intersection of research and production We're looking for a senior Applied AI/ML Scientist to help shape the future of fraud prevention and digital payments security.

This is a high-visibility, high-impact role where your models will directly reduce fraud losses, influence firmwide strategy, and power a scalable fraud prevention platform used across the organization.

You will:

• Design, train, and deploy advanced machine learning models for fraud prevention and risk management
• Research and implement cutting-edge architectures, including : Graph Networks, Agentic AI systems, Large Language Models (LLMs)
• Build and rigorously test AI agents to ensure reliability, robustness, and real-world effectiveness
• Develop scalable data pipelines and analytical tools using Databricks, PySpark, and AWS
• Monitor, optimize, and continuously evolve models to adapt to emerging fraud patterns
• Drive technical strategy and influence the analytical direction of the team
• Mentor junior scientists and promote engineering and modeling best practices
• Partner cross-functionally with Product, Engineering, and Data teams to align AI solutions with business impact
• Build reusable, production-grade ML frameworks that elevate firmwide fraud prevention capabilities

What You Bring

• Master's degree (or equivalent experience) in Computer Science, Statistics, Mathematics, Economics, or related quantitative field
• 10+ years of experience building and managing predictive risk models in financial institutions
• Strong foundation in machine learning theory (not just library usage)
• Hands-on experience with:
• Python, SQL, and/or PySpark
• PyTorch or TensorFlow
• XGBoost, Scikit-learn, or similar classical ML tools
• Experience working with large-scale datasets and distributed data processing
• Experience in AWS cloud environments
• Proven ability to take models from research production monitoring optimization
• Experience mentoring or coaching junior team members

Nice to Have

• Experience or strong interest in Graph Analytics and Agentic AI
• Knowledge of GSQL
• Experience working with both structured and unstructured data
• Product mindset — you understand that models are part of a broader user and business experience
• Passion for impact — your models making real-time financial decisions energizes you

Skills Required
Machine Learning, Tensorflow, Pyspark, Pytorch, Sql, XGBoost, Aws, Databricks, Python