Senior Data Scientist - LLMs for Fraud Detection

What you'll do

• Fine-tune and train models for fraud tasks, and build evaluation frameworks and production model serving.
• Create AI agents and tools to automate investigation, feature generation, and reporting.
• Manage detection models end to end, analyze fraud cases, and communicate findings through technical reports and trend analyses.

What they ask for

• Master’s or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 3+ years of hands-on experience in LLMs and large models or fraud and adversarial risk.
• Strong computer science fundamentals, deep learning and classic ML skills, and production ML experience.
• Strong Python and SQL; experience with Spark or PySpark and a cloud platform (AWS, GCP, or Azure).

Nice to have

• Publications at ML, NLP, or security venues.
• Experience with distributed training, inference optimization, retrieval-augmented systems, graph ML, or sequence modeling on behavioral data.

Pay

$140,000–$170,000 USD base salary

Tools

LLMs, PyTorch, Python, SQL, Spark, PySpark, AWS, GCP

AI focus

Apply LLMs, foundation models, and agentic AI to fraud detection, investigation automation, and related tasks; train, evaluate, and serve models in production.