Offer summary

Qualifications:

Bachelor's degree in a relevant field., Proven experience in developing web scrapers and crawlers., Strong proficiency in Python and JavaScript., Experience with machine learning models and data engineering tools..

Key responsibilities:

Develop and maintain web scrapers to extract news data.

Monitor and troubleshoot data extraction processes.

Deploy and oversee NLP models for classifying news articles.

Collaborate with teams to align data collection with organizational goals.

The Armed Conflict Location & Event Data Project (ACLED) is a disaggregated data collection, analysis, and crisis mapping project. ACLED is the highest quality and most widely used real-time data source on political violence and protest around the world. Practitioners, researchers, and governments depend on ACLED for the latest reliable information on current conflict and disorder patterns. ACLED’s aim is to capture the forms, actors, dates, and locations of political violence and protest as it occurs across states. The ACLED team conducts analysis to describe, explore, and test conflict scenarios, and makes both data and analysis open to use by the public. To read our analysis and download ACLED data, visit: www.acleddata.com. Please contact admin@acleddata.com with comments or queries regarding the ACLED dataset. To receive regular updates from ACLED with the latest data and analysis as it becomes available, subscribe to our mailing list at: www.acleddata.com/subscribe

About the organization

ACLED (Armed Conflict Location & Event Data) is a disaggregated data collection, analysis, and crisis mapping institution. The ACLED team collects conflict information, conducts analysis to describe, explore, and test conflict scenarios, and makes both data and analysis open for free use by the public. ACLED’s work is regularly used to inform journalism, academic research, and public discourse on conflict, and to support practitioners and policymakers. ACLED is the highest quality and most widely used realtime data and analysis source on political violence and protest around the world.

The Role:

ACLED is recruiting a Data Extraction Specialist to assist with the extraction and processing of news articles used to code ACLED events. The Data Extraction Specialist will work within ACLED’s Data Science team.

This position is fully remote and can be done from any location with reliable internet service. The preferred candidate’s time zone is GMT +1 (CET) to GMT 8 (Pacific time).

This position is open to nationals of any country. For more information, please review the Applicant FAQs . Please submit your salary range for consideration.

Specific tasks and responsibilities

The Data Extraction Specialist will be responsible for the following tasks:

Develop bespoke web scrapers and general web crawlers to extract data from online news sources.

Deploy and monitor the performance of scrapers and crawlers to ensure reliable and continuous data acquisition.

Implement logging and alerting systems for scraper performance and failures.

Maintain and troubleshoot existing scrapers and crawlers, adapting them to changes in website structures and data formats.

Deploy models and monitor MLNLP models for filtering and classifying extracted news articles.

Develop and deploy scalable data engineering pipelines using cloud platforms (preferably AWS), Docker, or serverless technologies.

Ensure all developed scrapers and crawlers adhere to best practices for web scraping, including ethical considerations and respect for website terms of service.

Document all configurations, assumptions, and limitations to ensure consistency and transparency.

Collaborate with other teams at ACLED to understand data needs and align scraper strategy with broader organizational goals.

Skills and competencies

Required

Proven experience in developing and deploying web scrapers and crawlers for production use.
Proven experience developing language models for practical applications.
Strong proficiency in Python and JavaScript.
Experience with major web scraping frameworks and libraries (Scrapy, Beautiful Soup, Selenium, Playwright, Puppeteer, etc.).
Experience deploying machine learning models, including transformersbased NLP models, for processing source texts.
Experience with data engineering tools and frameworks (e.g., Docker, Kubernetes, Airflow, Databricks).
Understanding of ethical and legal considerations in web scraping, including compliance with robots.txt and terms of service.
Experience working to deadlines with limited supervision.
An extremely high level of attention to detail.
Flexible team player, especially across a remote, global team.
Fluency in English.
Bachelors degree required.