Crawling and Data Mining Expert

1 week ago


Remote, India Wordliner GmbH Full time

About Wordliner:
Wordliner is a leading software development company specializing in the real estate sector. We provide cutting-edge solutions for real estate agents, helping them to manage listings, clients, and transactions more effectively. Our mission is to revolutionize the real estate industry through innovative technology.

Job Overview:
Key Responsibilities:

- Develop, implement, and maintain web crawlers to gather data from specified websites.
- Monitor and ensure the efficiency and effectiveness of data extraction processes.
- Process and clean the gathered data to ensure it meets quality standards.
- Integrate the cleaned data into the company's database.
- Collaborate with the development team to understand data requirements and deliver necessary data insights.
- Troubleshoot and resolve issues related to web crawling and data integration.

Required Qualifications:

- Bachelor’s degree in Computer Science, Data Science, or a related field.
- Proven experience in web crawling and data mining.
- Proficiency in programming languages such as Python, Java, or similar.
- Experience with web scraping frameworks like Scrapy, Beautiful Soup, Selenium, etc.
- Solid understanding of RESTful APIs and database systems (SQL/NoSQL).
- Strong problem-solving skills and attention to detail.
- Excellent communication and teamwork skills.

Preferred Qualifications:

- Experience in the real estate sector.
- Familiarity with cloud services like AWS, Google Cloud, or Azure.
- Knowledge of machine learning and data analysis tools.

Why You Should Join Us:
At Wordliner, you will be part of a forward-thinking company that is transforming the real estate industry. You will have the opportunity to work on challenging and rewarding projects, and your contributions will directly impact our clients' success. We value innovation, collaboration, and professional growth, and we are committed to providing our employees with a supportive and engaging work environment.

**Job Type**: Part-time

Expected hours: 20 per week

Schedule:

- Monday to Friday

Work Location: Remote


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