Socure

Data Scientist II, Fraud & Risk

$140K–$170K

Hub - San Francisco +3 · Hybrid · Full-time · Posted Oct 9, 2026

Location: Hub - San Francisco
Hub - Miami
Hub - New York
Hub - Seattle
Experience: 2-4 years developing and deploying deep learning models.
Education: Bachelor’s degree with substantial related experience, Master’s degree with relevant experience, or equivalent work background in Computer Science, Statistics, Mathematics, Engineering, or a related field.

About the job

Develop and deploy deep learning models for fraud detection, risk management, and identity verification across diverse data types.

Design and optimize deep learning models using varied data modalities and participate across the machine learning lifecycle, from data exploration through deployment.
Own assigned technical work with minimal supervision, making routine decisions and contributing to project goals.
Collaborate across teams and communicate results to technical and non-technical audiences.

2-4 years of hands-on experience developing and deploying deep learning models.
Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images.
Proficiency in Python and major ML libraries/frameworks, such as PyTorch, TensorFlow, or scikit-learn.
Foundational understanding of machine learning algorithms, model evaluation, and data pipeline development; experience deploying and monitoring production models.

Experience with LLMs and Agentic AI frameworks/infrastructure, such as LangChain, LangGraph, or Ray.
Experience in fraud prevention, risk modeling, or identity verification; real-time model inferencing experience is also a plus.

$140K – $170K USD base salary

Transformers, CNNs, LSTMs, Python, PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph/Ray

Develop deep learning models for fraud and risk challenges; the posting also lists LLMs and Agentic AI experience as a plus.

Model-written summary · the original posting is authoritative