About the role:TheSr. Fraud Data Analystis a key hire that will shape the future of Apollo's fraud and customer account security programs through data analysis and attribution techniques. While experience in behavioral fraud analytics is preferred, our team has successfully onboarded candidates with a diverse set of data analysis and data engineering backgrounds into fraud programs. This role has ample opportunity for upward mobility as Apollo's fraud decision engines accelerate and embrace advanced machine learning methodologies. The ideal candidate will have experience designing complex decision logic, designing backtesting programs and connecting disparate data sets. Effective communication skills and experience querying massive structured and unstructured data sets are required.Daily Adventures & Responsibilities:Participate in Complex Fraud InvestigationsProfile behavioral traits of advanced threat actors and search for associated accounts through behavioral analytics and data-based threat hunt techniques.Build Neo4j graph databases based on fingerprint attributes.Jump into the manual review and investigations queue when needed and to understand complex cases.Quantify Platform Abuse Impacts for PrioritizationDefine classes of malicious and opportunistic user groups and quantify abuse rates against newly discovered platform vulnerabilities.Work with cross-functional Product teams to validate discovered user classes and observed vulnerability behavior.Develop Robust Control LogicPerform backtesting on recommended control logic using Apollo's data lake, replication databases or sample data.Based on data-supporting investigations, implement control logic into Apollo's fraud control engine.Build Accurate Performance Alerts and DashboardsBuild cross-functional metrics and dashboards for control validation and performance tracking.Develop dynamic anomaly and volumetric alerts for Fraud Operations' response.Create self-service dashboards in BI tools for interrogation by cross-functional leadership.What We're Looking For:4+ years of experience in a data analyst, business intelligence or data engineering roleExperience building and configuring data pipelines from production data sources to replication services.Demonstrable SQL-based querying and NoSQL query scripting skills (Advanced queries requiring data mutation).Strong Python scripting experience, experience with data analysis libraries such as Pandas.Experience with MongoDB is required.Experience coaching semi and non-technical teams into junior data analytics roles a signficantt plus.An inquisitive and investigative nature: You are driven by curiosity and seek answers to problems by sifting through messages, logs and tangible evidence to understand the mindset and actions of an attacker.Willingness and desire to work independently and problem-solve with visionary guidance.Positive, learning mindset along with a detail-oriented, analytical approach to problem solving.You are excited about working remotely and have the skills and self-discipline to do so effectively.Good written and spoken English proficiency.Bonus Points:Chargebacks, disputes and ACH are familiar terms of which you understand the full lifecycle.Vendor relationship and service performance management - experience running proof-of concept projects.Familiarity with rules-based fraud rule development such as Stripe Radar.
