Staff Data Scientist - Fraud & Risk

The role

You will design, build, and optimize advanced deep learning models for fraud detection and risk management. You will lead technical initiatives, mentor peers, and work with diverse data types to drive impactful solutions.

What you will do

• Design, develop, and implement advanced deep learning models including transformers, CNNs/RNNs, and graph learning algorithms.
• Build and optimize models using tabular data, natural language, point clouds, and images.
• Lead the end-to-end machine learning lifecycle from data exploration to production monitoring.
• Take ownership of project outcomes, data quality, and delivery timelines.
• Mentor and share knowledge with peers and junior data scientists.
• Collaborate cross-functionally with Product, Engineering, and Risk teams.
• Conduct research to explore new data sources and develop novel algorithms.
• Present findings and recommendations to technical and executive stakeholders.
• Stay current with advancements in AI and machine learning.
• Model leadership competencies including continuous learning and accountability.

Required qualifications

• Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field; or equivalent professional experience.
• 8+ years of experience in data science, machine learning, or related fields.
• Experience in fraud prevention, risk modeling, or identity verification.
• Hands-on experience developing and deploying deep learning models (such as transformers, CNNs/RNNs, and graph learning).
• Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images.
• Strong proficiency in Python, SQL, and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
• Deep understanding of machine learning algorithms, model evaluation techniques, and data pipeline development.
• Experience with model deployment and monitoring in production environments.
• Demonstrated ability to proactively deliver complex outcomes, mentor others, and influence cross-functional decisions.
• Excellent communication skills to translate complex data problems into actionable business insights.
• Commitment to continuous learning, professional integrity, and high standards of business ethics.

Nice to have

• Specific experience with real-time model inferencing is a plus
• Experience with LLMs and Agentic AI framework/infrastructure (e.g., LangChain/LangGraph/Ray) is a plus

Before you apply

• We are unable to provide sponsorship now, or in the future.

About the company

Socure is building the identity trust infrastructure for the digital economy by verifying identities in real time and stopping fraud.