Staff Data Scientist

Role overview A Staff Data Scientist position focused on building advanced fraud detection models for an AI-powered risk decisioning platform that serves banks, fintechs, and digital-native organizations. The role joins an early-stage machine learning team with significant influence over the ML stack, blending deep technical work with cross-functional collaboration to protect online transactions from fraud and financial crime.

Responsibilities - Design, build, and deploy machine learning models that detect and prevent fraudulent activity across high-volume transaction streams - Partner with engineering, product, and operations teams to integrate detection models into production systems and workflows - Mine large-scale datasets to surface behavioral patterns, anomalies, and signals of emerging fraud tactics - Monitor, evaluate, and continuously retrain existing models to maintain performance against shifting threat landscapes - Track advances in fraud detection, applied ML, and statistical methods, translating relevant findings into platform improvements - Communicate model behavior, evaluation metrics, and analytical findings clearly to both technical peers and business stakeholders - Uphold data privacy and security standards throughout modeling, analysis, and deployment pipelines

Requirements - Three or more years of experience in data science or machine learning, with meaningful focus on fraud prevention, anti-money laundering, or related risk domains - Strong proficiency in Python for data analysis and model development - Solid grasp of ML algorithms and statistical techniques applied to classification, anomaly detection, or risk scoring - Hands-on experience with large datasets using distributed compute frameworks such as Apache Spark or Dask, including feature engineering and data quality work at scale - Analytical problem-solving skills with the ability to turn ambiguous signals into actionable insights - Clear communication skills for explaining complex technical work to non-technical audiences - Comfort working independently and collaboratively in a fast-paced, dynamic environment

Nice to have - Experience in fintech, marketplaces, or financial services - Familiarity with current fraud patterns, attacker tactics, and detection tooling - Cloud platform experience (AWS, GCP, or Azure) and MLOps practices

Benefits and work setup - Remote-first culture with the ability to work from anywhere - Competitive salary and equity, including a 401(k) - Employer-covered comprehensive health, dental, and vision insurance for employees and dependents (US) - Unlimited paid time off - Engineering- and product-led organization with leadership rooted in technical backgrounds - Family-friendly environment with regular team events and offsites - Strong emphasis on learning, professional growth, and mission-driven work protecting online transactions