Staff Data Scientist (Fraud & Risk)

Join Socure, a leading provider of digital identity verification and fraud prevention solutions. As a Staff Data Scientist, you will design, build, and optimize advanced machine learning models to enhance our fraud detection and risk management capabilities. You will lead technical initiatives, mentor peers, and collaborate cross-functionally to drive strategic decisions. This is a remote position with a comprehensive benefits package.

• Design, build, and optimize advanced data science and machine learning models for fraud detection and risk management.
• Lead technical initiatives, mentor peers, and drive functional productivity and project success within the Fraud & Risk Data Science team.
• Collaborate cross-functionally with Product, Engineering, and Risk teams to define data requirements and drive insights that guide strategic decisions.

• This role requires deep technical expertise, strategic ownership, and a commitment to Socure’s leadership principles, including continuous learning, effective communication, and accountability
• Excellent communication skills with the ability to translate complex data problems into actionable business insights for both technical and non-technical audiences
• Demonstrated ability to proactively deliver complex outcomes, mentor others, and influence cross-functional decisions
• Deep understanding of machine learning algorithms, model evaluation techniques, and data pipeline development
• Experience in fraud prevention, risk modeling, or identity verification
• Master’s or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field; or equivalent professional experience
• Strong proficiency in Python, SQL, and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Years of hands-on experience developing and deploying deep learning models (such as transformers, CNNs/RNNs, and graph learning)
• Experience with LLMs and Agentic AI framework/infrastructure (e.g., LangChain/LangGraph/Ray) is a plus
• Commitment to continuous learning, professional integrity, and high standards of business ethics
• Experience with model deployment and monitoring in production environments (specific experience with real-time model inferencing is a plus)
• Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images
• 8+ years of experience in data science, machine learning, or related fields, ideally in a high-growth tech or fintech environment