Summary To enhance user profiling and risk assessment, we are building web crawlers to collect relevant user data from third-party sources, forums, and the dark web. We are seeking a Senior Web Crawler & Data Extraction Engineer to design and implement these data collection solutions. Job Responsibilities Design, develop, and maintain web crawlers and scrapers to extract data from open web sources, forums, marketplaces, and the dark web. Implement data extraction pipelines that aggregate, clean, and structure data for fraud detection and risk profiling. Use Tor, VPNs, and other anonymization techniques to safely crawl the dark web while avoiding detection. Develop real-time monitoring solutions for tracking fraudulent activities, data breaches, and cybercrime discussions. Optimize crawling speed and ensure compliance with website terms of service, ethical standards, and legal frameworks. Integrate extracted data with fraud detection models, risk scoring algorithms, and cybersecurity intelligence tools. Work with data scientists and security analysts to develop threat intelligence dashboards from collected data. Implement anti-bot detection evasion techniques and handle CAPTCHAs using AI-driven solvers where necessary. Stay updated on OSINT (Open-Source Intelligence) techniques, web scraping best practices, and cybersecurity trends. Requirements 5+ years of experience in web crawling, data scraping, or cybersecurity data extraction. Strong proficiency in Python, Scrapy, Selenium, BeautifulSoup, Puppeteer, or similar frameworks. Experience working with Tor, proxies, and VPNs for anonymous web scraping. Deep understanding of HTTP protocols, web security, and bot detection mechanisms. Experience parsing structured and unstructured data from JSON, XML, and web pages. Strong knowledge of database management (SQL, NoSQL) for storing large-scale crawled data. Familiarity with AI/ML-based fraud detection techniques and data classification methods. Experience working with cybersecurity intelligence sources, dark web monitoring, and OSINT tools. Ability to implement scalable, distributed web crawling architectures. Knowledge of data privacy regulations (GDPR, CCPA) and ethical data collection practices. Nice to Have Experience in fintech, fraud detection, or threat intelligence. Knowledge of natural language processing (NLP) for analyzing cybercrime discussions. Familiarity with machine learning-driven anomaly detection for fraud prevention. Hands-on experience with cloud-based big data solutions (AWS, GCP, Azure, Elasticsearch, Kafka).
