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Socure is building identity trust infrastructure for the digital economy, verifying identities in real time and stopping fraud before it starts. We are seeking a Staff Data Scientist to join the Fraud & Risk Data Science team as an advanced-level individual contributor.
You will design, build, and optimize advanced deep learning models (transformers, CNNs/RNNs, graph learning) that power core fraud detection and risk management solutions. You will lead technical initiatives, mentor peers, and drive project success while working hands-on with complex ML systems.
Key responsibilities include:
- Design and implement advanced deep learning models for fraud detection and risk management across diverse data modalities (tabular, NLP, point clouds, images)
- Lead the end-to-end ML lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and production monitoring
- Take ownership of project outcomes, data quality, and delivery timelines
- Mentor junior data scientists and share knowledge across the team
- Collaborate cross-functionally with Product, Engineering, and Risk teams to define data requirements and drive strategic insights
- Conduct research to explore new data sources and develop novel algorithms
- Present findings to technical and executive stakeholders
- Stay current with AI/ML advancements and apply innovative approaches to real-world problems
- Model leadership competencies: continuous learning, communication, accountability, team development, decision-making, and change management
Requirements:
- Master's or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, or related field; or equivalent professional experience
- 8+ years in data science, machine learning, or related fields, ideally in high-growth tech or fintech
- Experience in fraud prevention, risk modeling, or identity verification
- Hands-on experience developing and deploying deep learning models (transformers, CNNs/RNNs, graph learning)
- Experience with diverse data modalities: tabular data, text/language, point clouds, images
- Strong proficiency in Python, SQL, and major ML libraries/frameworks (PyTorch, TensorFlow, scikit-learn)
- Deep understanding of ML algorithms, model evaluation techniques, and data pipeline development
- Experience with model deployment and monitoring in production environments (real-time inferencing a plus)
- Experience with LLMs and Agentic AI frameworks (LangChain/LangGraph/Ray) is a plus
- Demonstrated ability to deliver complex outcomes, mentor others, and influence cross-functional decisions
- Excellent communication skills translating complex data problems into actionable business insights
- Commitment to continuous learning, professional integrity, and high ethical standards
