We are seeking a highly analytical Ad Fraud Analyst or PPC Forensic Specialist to assist with high-level traffic auditing for Google Ads and Meta Ads. Your primary responsibility will be to identify and document "Ad-Waste" by analyzing discrepancies between billed ad clicks and real-user engagement data. We are not looking for campaign optimization (ROAS/Bidding); we are looking for a forensic expert who can prove when traffic is non-human. Key Responsibilities: Forensic Auditing: Manually and programmatically audit client traffic to identify General Invalid Traffic (GIVT) and Sophisticated Invalid Traffic (SIVT). Data Cross-Referencing: Match Google Click IDs (GCLIDs) and Meta IDs from ad dashboards with raw server logs (Apache/Nginx) or tracking scripts to extract IP addresses and user-agent data. Behavioral Anomaly Detection: Identify clusters of fraudulent behavior, including temporal bursts, data-center IP ranges (ASN lookup), and zero-intent signals (session duration: 3s, 100% bounce rates). Evidence Pack Generation: Create structured, verifiable "Case Files" that include cluster tables of suspicious activity, forensic IP logs, and behavioral proof of non-human interaction. Gap Analysis: Compare platform-credited "Invalid Activity" against your findings. Required Skills: Deep understanding of Invalid Traffic (IVT) and (SIVT) patterns. Expertise in cross-referencing GCLIDs with server-side logs to find the "identity" of a click. Proficiency in Excel (Pivot Tables/Clustering) or Python for parsing large traffic datasets. Familiarity with IP reputation databases and ASN lookups (e.g., identifying traffic from AWS, Azure, or known proxy networks). Knowledge of technical bot indicators like navigator.webdriver properties or mismatched packet headers. Preferred Experience: Previous experience working in Ad Ops or Cybersecurity Fraud Detection. Ability to package data into clean, legalistic PDF/CSV dossiers for review.