Senior Data Scientist, FinCrime
Core
Build the intelligence layer for ARQ's financial products by developing machine learning models to detect fraud, prevent losses, and manage risk at scale.
Role type
Senior IC machine-learning engineer (financial crime)
Builds
Production ML models for fraud detection, chargeback prediction, anomaly detection, identity verification, and transaction monitoring.
Domain
Fintech / Financial Services / Financial Crime
Deliverable
production ML models
Required skills
Python, large-scale dataset processing, supervised learning (classification), anomaly detection, fraud prevention, risk modeling, data pipeline construction, model-serving solutions, model performance monitoring, cross-functional collaboration
Preferred skills
Financial crime/AML/risk domain experience, fintech/banking background, backend engineering, real-time decisioning platforms, MLOps practices
Technologies
Python
Responsibilities
Design, build, and deploy ML models for financial crime challenges; Transform business problems into measurable ML solutions; Partner with Product and Operations to define requirements and metrics; Analyze large datasets to identify patterns and risks; Build and maintain production-ready data pipelines; Monitor and improve model accuracy and business impact; Collaborate with Data and Backend Engineering to operationalize ML at scale.
Seniority
Senior, hands-on IC
