Senior Data Scientist

Role Overview

We're working with a client looking for a Senior Data Scientist to lead the development of next-generation machine learning solutions that power fraud prevention and risk decisioning products. This is a highly technical role with significant ownership, combining hands-on model development, research, cross-functional leadership, and mentorship.

Key Responsibilities

• Develop and improve machine learning and deep learning models focused on fraud detection, identity intelligence, and risk management.
• Design solutions using advanced techniques such as transformers, graph-based learning, neural networks, and other modern AI approaches.
• Lead the full lifecycle of data science initiatives, including data exploration, feature creation, model training, validation, deployment, and performance monitoring.
• Work with a variety of data types including structured datasets, text, images, behavioral signals, and other complex inputs.
• Partner closely with Product, Engineering, and Risk teams to identify opportunities for data-driven improvements.
• Research emerging methodologies and new data sources to strengthen detection capabilities and stay ahead of evolving fraud patterns.
• Mentor other data scientists and contribute to best practices across the organization.
• Present technical insights and recommendations to both business leaders and technical stakeholders.

Requirements

• Advanced degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field, or equivalent practical experience.
• 8+ years of experience building machine learning or data science solutions in production environments.
• Background working on fraud prevention, risk analytics, identity verification, financial crime, trust & safety, or similar domains.
• Strong proficiency with Python, SQL, and modern machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience deploying and maintaining large-scale machine learning systems.
• Deep understanding of model evaluation, experimentation, feature engineering, and data pipeline development.
• Proven ability to drive complex projects independently and influence technical direction across teams.
• Excellent communication skills with the ability to translate technical concepts into business impact.

Preferred

• Experience working with large language models, agent-based AI systems, or orchestration frameworks.
• Familiarity with NLP, computer vision, graph learning, or multimodal machine learning techniques.
• Experience in high-growth technology, fintech, cybersecurity, fraud, or digital identity environments.
• Track record of delivering research-driven innovations that improve business results.

Location: Remote (United States)

Compensation: Competitive base salary, equity, and comprehensive benefits package.