Data Scientist I

requirements etc. We are looking at implementing an AI based solution to support increased transaction monitoring for AML activities. If you are the one who enjoys solving problems in a challenging environment, and who has the desire to take their career to the next level. If any of these opportunities excite you, we would love to talk. Role

• Implement generative AI models and applications for AML transaction monitoring use cases.
• Build advanced solutions leveraging Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), tool calling, and Lang Chain/Lang Graph for dynamic workflows.
• Develop machine learning pipelines for fine-tuning large language models (LLMs) and other foundation models.
• Implement content generation systems for text, image, and multimodal outputs.
• Apply computer vision techniques for image analysis, creative generation, and visual search.
• Implement evaluation frameworks for Gen AI applications, including hallucination detection, bias checks, and quality scoring.
• Build observability and monitoring solutions for AI systems, including latency, cost tracking, and model performance metrics.
• Build scalable solutions on cloud platforms (AWS, Azure) and leverage data platforms like Databricks.
• Integrate AI models into production systems with a focus on performance, security, and compliance.
• Stay current with the latest advancements in AI/ML research, particularly in generative AI, and apply them to real-world problems.
• Promote engineering best practices and contribute to a culture of innovation and collaboration.

All About You

• Has strong knowledge in building and deploying generative AI solutions (e.g., LLMs, diffusion models, transformers).
• Expertise in RAG pipelines, MCP-based integrations, tool calling frameworks, and Lang Chain/Lang Graph.
• Proficiency in Python and popular AI/ML frameworks such as Py Torch or Tensor Flow.
• Experience with content generation systems (text, image, multimodal) and computer vision models.
• Exposure to evaluation techniques for Gen AI (e.g., hallucination detection, factuality scoring, bias evaluation).
• Knowledge of observability tools for AI systems (e.g., monitoring latency, cost, and performance metrics).
• Exposure to MLOps practices, including model versioning, CI/CD for ML, and monitoring in production.
• Exposure to cloud platforms (AWS, Azure) and data engineering tools like Databricks.
• Solid understanding of prompt engineering, fine-tuning, and model evaluation techniques.
• Knowledge of API development and integration of AI models into web or mobile applications.
• Strong problem-solving skills and ability to work in a fast-paced, high-impact environment.
• Excellent communication and collaboration skills to work effectively with technical and non-technical stakeholders.

EDUCATION:

• Bachelor or Master's Degree in Computer Science or equivalent Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.