Security Research (Fraud Detection)

Location: Hybrid in Tel Aviv-Yafo, Gush Dan, Israel

Company

hirify.global provides a SaaS platform combining customer identity management, identity verification, and fraud prevention for consumer-facing industries.

What you will do

• Research fraud and abuse techniques including account takeover, bots, phishing, social engineering, device spoofing, emulators, remote access tools, and suspicious network infrastructure.
• Identify and validate new data collection opportunities, behavioral patterns, device indicators, browser indicators, and mobile application signals.
• Analyze telemetry, customer-provided labels, behavioral data, device signals, network indicators, and attack patterns to identify detection opportunities.
• Reproduce attacker techniques, generate telemetry, identify detection gaps, and translate research findings into detection and prevention logic.
• Build Python-based research infrastructure, analysis workflows, internal tools, and model-ready data features.
• Collaborate with data science, engineering, and product teams to validate, implement, monitor, and improve production detection capabilities.

Requirements

• At least 3 years of experience in security research, fraud research, detection engineering, threat research, mobile security, browser security, or a similar technical role.
• Bachelor’s degree in Computer Science, Cybersecurity, Data Science, or a related field, or equivalent hands-on experience.
• Hands-on experience with desktop or mobile browsers, browser APIs and automation, browser fingerprinting, native Android or iOS applications, mobile security, emulators, or mobile instrumentation.
• Strong understanding of web and mobile technologies, APIs, application behavior, and modern attack techniques.
• Strong Python skills for research tools, automation, data analysis, detection prototypes, or feature engineering pipelines.
• Knowledge of machine learning training and validation concepts, including overfitting, leakage, feature quality, precision, recall, and model evaluation.

Nice to have

• Experience with both browser-based and mobile-native research.
• Knowledge of account takeover, identity theft, payment fraud, credential stuffing, scraping, bots, automation frameworks, and anti-detection techniques.
• Experience with browser internals, JavaScript runtime behavior, DOM APIs, WebView behavior, headless browsers, mobile app instrumentation, hooking, repackaging, or anti-tampering.
• Experience with fingerprinting, device intelligence, behavioral biometrics, malware analysis, phishing kits, remote access tools, or underground fraud ecosystems.
• Experience with pandas, SQL, notebooks, data visualization, detection quality measurement, model evaluation, or production monitoring.

Culture & Benefits

• Hybrid work arrangement in Tel Aviv-Yafo, Gush Dan, Israel.
• Hands-on work with messy real-world data and modern fraud and abuse challenges.
• Close collaboration with engineering, product, data science, and machine learning teams.
• Opportunity to develop practical defenses and customer-facing fraud prevention capabilities.