Data Scientist I – Generative AI for AML

About the role

Mastercard’s Global Risk and Compliance team is building an AI‑driven solution to enhance transaction monitoring for anti‑money‑laundering (AML) activities. As a Data Scientist I you will work on cutting‑edge generative AI models and integrate them into production workflows.

Key responsibilities

• Implement generative AI models and applications for AML transaction monitoring use cases.
• Build advanced solutions using Retrieval‑Augmented Generation (RAG), Model Context Protocol (MCP), tool calling, and LangChain/LangGraph for dynamic workflows.
• Develop machine‑learning pipelines for fine‑tuning large language models (LLMs) and other foundation models.
• Create content‑generation systems for text, image, and multimodal outputs.
• Apply computer‑vision techniques for image analysis, creative generation, and visual search.
• Design evaluation frameworks for GenAI applications, including hallucination detection, bias checks, and quality scoring.
• Implement observability and monitoring for AI systems, tracking latency, cost, and model performance metrics.
• Deploy scalable solutions on cloud platforms (AWS, Azure) and leverage data platforms such as Databricks.
• Integrate AI models into production systems with a focus on performance, security, and compliance.
• Stay current with the latest generative AI research and apply findings to real‑world problems.

Required profile

• Enjoys solving complex problems in a challenging environment.
• Motivated to advance a career in AI/ML and generative technologies.

Required skills

• Generative AI model development
• Retrieval‑Augmented Generation (RAG)
• Model Context Protocol (MCP)
• LangChain / LangGraph
• Large language model (LLM) fine‑tuning
• Computer‑vision techniques
• Evaluation frameworks for hallucination detection, bias assessment, and quality scoring
• Observability and monitoring of AI systems
• Cloud platforms: AWS, Azure
• Data platforms: Databricks