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Web Scraping Analyst
hace 3 semanas
**I. Position Summary**:
The **Web Scraping Analyst** will lead the development and execution of data collection pipelines by extracting structured information from websites and directories. This role is responsible for building and maintaining web scraping scripts and ensuring the accuracy, usability, and consistency of the output data across internal use cases.
**II. Key Responsibilities**:
- **Web Scraping Development**
Develop and maintain scalable web scraping scripts using Python (e.g., BeautifulSoup, Scrapy, Selenium) to extract data from multi-page directories and detailed company listings.
- **Data Output and Formatting**
Create structured Excel/CSV outputs with required fields such as company name, country, website, LinkedIn, city, and state.
- **Data Quality and Analysis**
Analyze scraped data to identify patterns, gaps, or inconsistencies and ensure outputs are aligned with project goals. Perform thorough quality checks and validate data before delivery.
- **Scraping Automation and Monitoring**
Schedule, monitor, and maintain scraping jobs to ensure consistent data extraction and uptime.
- **Collaboration and Requirement Gathering**
Collaborate with internal teams to define data needs and translate requirements into actionable scraping tasks.
- **Performance Optimization**
Continuously improve the performance and scalability of scraping tools and workflows.
- **Security and Confidentiality**
Handle all data and scraping activities in a secure manner, ensuring protection of sensitive or proprietary data in line with internal policies.
**III. Qualifications**:
**Education**:
- Bachelor’s degree in Computer Science, Data Science, Information Technology, or a related field (or equivalent experience).
**Experience**:
- Min. of 3 years of experience in web scraping, automation scripting, or data extraction.
- Demonstrated experience extracting data from structured and unstructured sources such as business directories, vendor lists, and company profiles (e.g., Crunchbase).
**Technical Skills**:
- Proficiency in Python and web scraping libraries such as BeautifulSoup, Scrapy, Selenium, and Pandas.
- Experience working with Excel and CSV file generation using Python.
- Familiarity with HTML, CSS selectors, XPath, and JSON structures.
- Basic knowledge of databases (SQL, MongoDB) and APIs.
- Familiarity with version control tools like Git.
**Soft Skills**:
- Detail-oriented and committed to data accuracy.
- Self-motivated with strong time management skills.
- Ability to communicate effectively with both technical and non-technical team members.
- Proactive and resourceful when troubleshooting scraping issues or adapting to website changes.
**Certifications**:
- Certifications in Python, data scraping, or data analysis (preferred but not required).
**IV. Competencies**:
- **Execution Focus**: Delivers structured, high-quality data outputs with precision.
- **Problem Solving**: Efficiently resolves scraping errors and adapts to website changes.
- **Process Efficiency**: Builds reusable, optimized scraping solutions.
- **Data Integrity**: Ensures thorough validation and accuracy in all extracted datasets.
- **Adaptability**: Responds well to changing requirements and new data environments.
- **Documentation Discipline**: Clearly documents logic, updates, and project flow for repeatability.
**V. Work Environment**:
**Work Conditions**: Fully remote work
**Work Hours**: Standard business hours with flexibility; availability to work extended hours during active deal cycles.
