About the job
We are looking for a seasoned Senior Data Scientist with deep expertise in risk modeling and fraud strategy to join our team. In this role, you will design, build, and operationalize advanced machine learning and AI-driven models that power our risk decisioning and fraud prevention capabilities. You will work closely with fraud strategy, product, and engineering teams to translate complex data signals into actionable risk frameworks — ensuring our systems are not only accurate but adaptive to evolving threat landscapes. Beyond model development, you will play a key role in modernizing our monitoring and alerting infrastructure, leveraging AI to proactively detect anomalies, reduce false positives, and improve the speed and precision of risk interventions. You will mentor junior data scientists and be a strategic thought partner to stakeholders, driving a culture of rigor, experimentation, and continuous improvement.
Responsibilities
Lead and manage data science projects, ensuring timely delivery and alignment with business goals.
Develop and maintain data models, algorithms, and reporting systems to support data analysis and decision-making.
Analyze complex datasets to identify trends, patterns, and insights that drive strategic initiatives.
Collaborate with cross-functional teams to understand data needs and provide actionable insights.
Ensure data quality and integrity through regular audits and validation processes.
Mentor and guide junior data scientists, fostering a culture of continuous learning and improvement.
Qualifications
Minimum
5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
Preferred
10+ years of data science experience
Proven experience building and deploying risk models in production environments
Strong understanding of fraud strategy lifecycle — how model scores translate into rules, thresholds, decline/accept decisions, and case management workflows.
Familiarity with model explainability (SHAP, LIME, etc.) and the ability to communicate model behavior to non-technical fraud strategy and compliance stakeholders.
Experience working with transaction-level data at scale (e.g., payments, e-commerce, fintech) is strongly preferred.