Staff Data Scientist - Fraud & Risk

What you'll do

• Design, build, and optimize deep-learning models across varied data types, and lead the machine-learning lifecycle through production monitoring.
• Lead technical initiatives, research new data sources and algorithms, and collaborate with Product, Engineering, and Risk teams.
• Mentor peers and junior data scientists and present findings to technical and executive stakeholders.

What they ask for

• Experience in fraud prevention, risk modeling, or identity verification.
• Hands-on experience developing and deploying deep-learning models and working with diverse data modalities.
• Proficiency in Python, SQL, and major ML libraries/frameworks; deep understanding of ML algorithms, evaluation, and data pipelines.
• Experience deploying and monitoring models in production; ability to deliver complex outcomes, mentor others, and influence cross-functional decisions.

Nice to have

• Experience with real-time model inferencing.
• Experience with LLMs and Agentic AI frameworks or infrastructure, such as LangChain/LangGraph/Ray.

Pay

$191K – $230K USD base salary

Tools

Python, SQL, PyTorch, TensorFlow, scikit-learn, transformers, CNNs/RNNs, LangChain/LangGraph/Ray

AI focus

Develop and deploy deep-learning models for fraud and risk, including transformers, CNNs/RNNs, and graph learning; work with diverse data modalities. LLMs and Agentic AI are a plus.