Data scientist jobs in New York, NY

About the role

Socure is the leading provider of digital identity verification and fraud prevention solutions, leveraging AI and machine learning to power the most accurate identity trust decisions. Our mission is to eliminate identity fraud and ensure online trust across industries. We are seeking a Senior Data Scientist to join our Digital Intelligence team. In this role, you will drive the development of machine learning features and models that leverage device, network, and behavioral data to power fraud prevention and identity verification. You’ll work with rich, high-volume data from browser, mobile, and API traffic to surface meaningful insights and scalable risk signals. This is a great opportunity to own impactful projects, collaborate cross-functionally, and deepen your expertise in applied ML for device and behavioral intelligence. We are seeking a Senior Data Scientist to join our Digital Intelligence team. In this role, you will drive the development of machine learning features and models that leverage device, network, and behavioral data to power fraud prevention and identity verification. This is a great opportunity to own impactful projects, collaborate cross-functionally, and deepen your expertise in applied ML for device and behavioral intelligence.

What you'll bring

• Master’s degree (or equivalent practical experience) in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• 6+ years of experience in data science or applied machine learning, including experience working in production environments.
• Excellent SQL skills and extensive experience with large-scale databases and data modeling.
• Proven track record of deploying and maintaining ML models in live systems
• Proficiency in Python and distributed computing tools (e.g., Spark, PySpark).
• Hands-on experience with ML frameworks such as scikit-learn, XGBoost, TensorFlow, or similar.
• Excellent communication skills—able to explain complex technical results to non-technical stakeholders and senior leadership.
• Experience designing and interpreting experiments, working with real-world noisy datasets, and applying sound validation techniques to assess model robustness.
• Demonstrated ability to break down ambiguous problems, apply analytical rigor, and uncover meaningful insights that influence product or risk strategies.
• Strong judgment across data quality, model selection, and business impact tradeoffs.
• Collaborative mindset and experience working cross-functionally with product, engineering, and analytics teams.
• Background in fraud detection, behavioral biometrics, anomaly detection, or adversarial modeling.

Locations