[Hiring] Web Scraping Specialist @Wynd Labs

Role Description

We are seeking a Web Scraping Specialist who is proficient and brings significant experience in data extraction and web scraping techniques. You will join a small, specialized team and lead efforts to gather and analyze data, optimize scraping processes, and support our vision for a future where Grass plays a crucial role in transforming internet data accessibility.

Qualifications

• Demonstrated ability to extract data from complex websites with minimal supervision, with a portfolio or examples of past projects.
• Proficiency in languages such as Python or JavaScript, with strong skills in libraries and frameworks like BeautifulSoup, Scrapy, or Selenium.
• Knowledge of asynchronous programming, multithreading, and distributed scraping.
• In-depth knowledge of HTML, CSS, JavaScript, and the Document Object Model (DOM).
• Experience with NoSQL databases (MongoDB, Cassandra), capable of designing efficient storage solutions and managing data integrity.
• Ability to apply machine learning algorithms for data cleaning, categorization, or predictive analysis adds significant value.
• Experience with cloud services (AWS, Google Cloud, Azure) for deploying and managing scraping jobs at scale.
• Active participation in open-source projects related to web scraping, data processing, or similar fields.

Requirements

• Write, test, and refine code that extracts data from various online sources, ensuring reliability and efficiency.
• Perform data retrieval tasks, handling complexities such as pagination and dynamic content loaded with AJAX.
• Clean and format extracted data, ensuring it meets quality standards for further analysis or processing.
• Database management: Store and manage the scraped data in appropriate databases, optimizing for access speed and data integrity.
• Regularly monitor the scraping processes, identify and resolve any issues to maintain continuous data flow.

Benefits

• Opportunity to be at the forefront of developing a web-scale crawler and knowledge graph that improves access to public web data and extends the value of AI to the people.
• A culture of a lean team with a high bar, focused on capability and meaningful work.
• Prioritization of low ego and high output in a fully remote team.
• Competitive salary, benefits, and equity package.