Web Scraping Specialist

Web Scraping Specialist

$70k – $140k

Who We Are.

Wynd Labs is an early-stage startup that is on a mission to make public web data accessible for AI through contributions to Grass.

Grass is a network sharing application that allows users to share their unused bandwidth. Effectively, this is a residential proxy network that directly rewards individual residential IPs for the bandwidth they provide. Grass will route traffic equitably among its network and meter the amount of data that each node provides to fairly distribute rewards.

In non-technical terms: Grass unlocks everyone's ability to earn rewards by simply sharing their unused internet bandwidth on personal devices (laptops, smartphones).

This project is for those who lead with initiative and seek to challenge themselves and thrive on curiosity.

We operate with a lean, highly motivated team who revel in the responsibility that comes with autonomy. We have a flat organizational structure, the people making decisions are also the ones implementing them. We are driven by ambitious goals and a strong sense of urgency. Leadership is given to those who show initiative, consistently deliver excellence and bring the best out of those around them. Join us if you want to set the tone for a fair and equitable internet.

The Role.

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.

Who You Are.

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.

What You'll Be Doing.

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.

Why Work With Us.

Opportunity. We are at at the forefront of developing a web-scale crawler and knowledge graph that allows ordinary people to participate in the process, and share in the benefits of AI development.

Culture. We’re a lean team working together to achieve a very ambitious goal of improving access to public web data and distributing the value of AI to the people. We prioritize low ego and high output.

Compensation. You’ll receive a competitive salary and equity package.

Qualifications

Remote, Significant experience in data extraction, Web scraping techniques, Extract data from complex websites, Portfolio or examples of past projects, Python, JavaScript, BeautifulSoup, Scrapy, Selenium, Asynchronous programming, Multithreading, Distributed scraping, HTML, CSS, JavaScript, Document Object Model (DOM), NoSQL databases, MongoDB, Cassandra, Designing efficient storage solutions, Managing data integrity, Machine learning algorithms for data cleaning, categorization, or predictive analysis (adds value), Cloud services (AWS, Google Cloud, Azure), Deploying and managing scraping jobs at scale, Active participation in open-source projects, Data cleaning, Data formatting, Database management, Monitoring scraping processes, Identifying and resolving issues