Staff Data Scientist - Fraud & RiskJob OverviewWe are seeking a skilled and motivated Staff Data Scientist to join our Fraud & Risk Data Science team. As an advanced-level individual contributor, you will design, build, and optimize advanced DS/ML models that power our core fraud detection and risk management solutions. You will lead technical initiatives, mentor peers, and drive functional productivity and project success. You will work hands-on with advanced deep learning models, driving delivery of impactful solutions for fraud detection, risk management, and identity verification. This role requires deep technical expertise, strategic ownership, and a commitment to Socure's leadership principles, including continuous learning, effective communication, and accountability.
Job Responsibilities- Design, develop, and implement advanced deep learning models, including transformers, CNNs/RNNs, and graph learning algorithms, to address complex fraud and risk challenges.
- Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images.
- Lead the end-to-end machine learning lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and monitoring in production environments.
- Take ownership of project outcomes, data quality, and delivery timelines; proactively escalate issues and work collaboratively to resolve challenges.
- Mentor and share knowledge with peers and junior data scientists, fostering a culture of experimentation, rapid iteration, and continuous learning.
- Collaborate cross-functionally with Product, Engineering, and Risk teams to define data requirements and drive insights that guide strategic decisions.
- Conduct in-depth research to explore new data sources and develop novel algorithms that advance the state of the art in fraud detection.
- Present findings and recommendations to technical and executive stakeholders with clarity and influence.
- Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems.
- Model Socure's embedded leadership competencies: continuous learning, effective communication, accountability, team development, decision making, and managing change.
Job Requirements- 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, ideally in a high-growth tech or fintech environment.
- Experience in fraud prevention, risk modeling, or identity verification.
- Years of 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 (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.
- Demonstrated ability to proactively deliver complex outcomes, mentor others, and influence cross-functional decisions.
- Excellent communication skills with the ability to translate complex data problems into actionable business insights for both technical and non-technical audiences.
- Commitment to continuous learning, professional integrity, and high standards of business ethics.
