Python Developer for Web Scraping with Proxies, Dark Web Expertise, NLP, and Machine Learning Integration
Budget: ₹37,500 – ₹75,000 INR
I'm looking for an experienced Python developer with advanced web scraping expertise, including the use of proxies and dark web scraping techniques. In addition to traditional scraping, the candidate should also be proficient in applying Natural Language Processing (NLP) and Machine Learning (ML) techniques to extract, analyze, and process the scraped data. The data must be delivered in JSON format, ensuring structured, accurate, and meaningful insights.
Responsibilities:
1. Develop and maintain Python-based web scraping scripts for complex websites and dark web resources using proxies.
2. Utilize NLP techniques to extract and process text-based data, such as named entity recognition (NER), sentiment analysis, and topic modeling.
3. Integrate machine learning models to improve the quality, relevance, and efficiency of the scraped data (e.g., text classification, clustering, or prediction algorithms).
4. Implement proxy rotation strategies to bypass anti-scraping mechanisms and avoid detection.
5. Scrape data from dark web resources securely, adhering to ethical guidelines and ensuring anonymity.
6. Structure the scraped and processed data in JSON format for seamless integration with other systems.
7. Continuously improve scraping processes and enhance performance using AI-based approaches.
Requirements:
Proven experience in Python-based web scraping (minimum 2 years).
Proficiency with scraping libraries like BeautifulSoup, Scrapy, Requests, and Selenium.
Strong experience with proxy management and techniques to overcome anti-bot mechanisms.
Expertise in dark web scraping, including working with the Tor network and Onion services.
Hands-on experience with NLP libraries such as SpaCy, NLTK, or Hugging Face for processing textual data.
Knowledge of Machine Learning frameworks such as TensorFlow, PyTorch, or Scikit-learn to apply models for data extraction and analysis.
Experience in handling unstructured and semi-structured data and transforming it into a structured JSON format.
Strong understanding of web protocols, dynamic content handling, and security aspects related to web scraping.
Responsibilities:
1. Develop and maintain Python-based web scraping scripts for complex websites and dark web resources using proxies.
2. Utilize NLP techniques to extract and process text-based data, such as named entity recognition (NER), sentiment analysis, and topic modeling.
3. Integrate machine learning models to improve the quality, relevance, and efficiency of the scraped data (e.g., text classification, clustering, or prediction algorithms).
4. Implement proxy rotation strategies to bypass anti-scraping mechanisms and avoid detection.
5. Scrape data from dark web resources securely, adhering to ethical guidelines and ensuring anonymity.
6. Structure the scraped and processed data in JSON format for seamless integration with other systems.
7. Continuously improve scraping processes and enhance performance using AI-based approaches.
Requirements:
Proven experience in Python-based web scraping (minimum 2 years).
Proficiency with scraping libraries like BeautifulSoup, Scrapy, Requests, and Selenium.
Strong experience with proxy management and techniques to overcome anti-bot mechanisms.
Expertise in dark web scraping, including working with the Tor network and Onion services.
Hands-on experience with NLP libraries such as SpaCy, NLTK, or Hugging Face for processing textual data.
Knowledge of Machine Learning frameworks such as TensorFlow, PyTorch, or Scikit-learn to apply models for data extraction and analysis.
Experience in handling unstructured and semi-structured data and transforming it into a structured JSON format.
Strong understanding of web protocols, dynamic content handling, and security aspects related to web scraping.