Web Scraper remote

Web Scraper remote

50 openings

$20 - $50/hr

Required Skills

Python

Scrapy

Selenium

Html

Css

Javascript

Rest-api

Json

Xml

Data-cleaning

Data-manipulation

Nosql

Relational-databases

Web-security

Job Description

Job Title: Web Scraper

Job Type: Contractor (Part-time)

Location: Remote

Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Key Responsibilities:

- Design, develop, and maintain robust web scraping scripts and applications

- Perform data extraction from multiple websites, handling both static and dynamic content

- Clean, validate, and structure large volumes of scraped data for further analysis

- Monitor scraping pipelines for data quality and troubleshoot scraping failures

- Implement solutions to bypass anti-scraping mechanisms and maintain scraping effectiveness

- Collaborate with customer's team members to define data requirements and deliverables

- Document scraping processes and maintain code for scalability and reusability

Required Skills and Qualifications:

- Proven experience in building and maintaining web scrapers using tools such as Python, Scrapy, Selenium, or similar technologies

- Strong understanding of HTML, CSS, JavaScript, and web protocols

- Expertise in handling APIs, RESTful interfaces, and parsing JSON/XML data

- Excellent written and verbal communication skills, with the ability to convey technical information clearly

- Proficiency with data cleaning, manipulation, and storage using relational or NoSQL databases

- Knowledge of web security concepts and best practices for ethical scraping

- Demonstrated ability to troubleshoot and resolve issues autonomously

Preferred Qualifications:

- Experience with cloud-based scraping and deployment (AWS, Azure, or GCP)

- Familiarity with version control systems like Git

- Background in large-scale data extraction projects