Information Extraction Specialist

About the role

The Information Extraction Specialist is responsible for turning unstructured and semi‑structured data sources—such as documents, reports, web content, databases, and multimedia files—into clean, structured datasets. The role combines natural language processing, machine‑learning models, rule‑based systems, and data‑processing techniques to deliver high‑quality, usable information for downstream applications.

Key responsibilities

• Design and implement extraction pipelines for diverse document types, including legal contracts, medical records, financial reports, news articles, and technical documentation.
• Create and manage high‑quality training datasets, define sampling strategies, lead annotation teams, and ensure rigorous quality assurance.
• Evaluate model performance using precision, recall, and F1 metrics; analyze errors and iterate on guidelines, data, or model architecture.
• Assess, integrate, and customize open‑source and commercial information extraction tools and platforms.
• Develop scripts and automated workflows to streamline the extraction process.
• Adapt extraction systems to new domains quickly, acquiring necessary domain knowledge and updating guidelines.

Required profile

• Minimum 5 years of experience in information extraction, NLP, computational linguistics, or related fields.
• Strong problem‑solving abilities with a track record of analyzing model errors and proposing data‑driven improvements.
• Excellent written and verbal communication in English, with the ability to document complex guidelines clearly.
• Proven experience designing annotation schemas and handling edge cases.

Required skills

• Python for data analysis and NLP tasks.
• spaCy, NLTK, Hugging Face Transformers, Stanford CoreNLP.