Champion a data-first approach across internal teams and client engagements, promoting clarity and impact
Build and deploy machine learning models to prevent fraud across diverse fintech use cases
Use data and models to support the development of risk mitigation strategies and interventions while preserving and improving the user experience
Work directly with clients to understand challenges and deliver high-impact, data-driven solutions
Evolve our risk metrics, the supporting datasets, and how we measure the causal impact of initiatives
Collaborate with engineering to scale models into production and optimize performance

5+ years of experience in data science or quantitative modeling, ideally in risk or fraud contexts
Strong working knowledge of Python, R, Spark, SQL, or equivalent
Sharp critical thinking and creative problem-solving skills with a bias toward action
Proven ability to explain complex technical findings to non-technical stakeholders and clients

Data Scientist – Fraud Post Sales

Key skills