Information Extraction Specialist

About the role

The Information Extraction Specialist will design, build, and maintain pipelines that transform unstructured and semi‑structured data into structured, actionable datasets. Working remotely, you will apply NLP, machine‑learning, and rule‑based techniques to a variety of document types across domains such as legal, medical, finance, and technical documentation.

Key responsibilities

• Design and implement end‑to‑end information extraction pipelines for diverse document sources.
• Lead the creation of high‑quality training datasets, including annotation schema design, team coordination, and quality assurance.
• Evaluate model performance using precision, recall, F1 and iterate on data, guidelines, or model architecture.
• Assess, integrate, and customize open‑source and commercial extraction tools and platforms.
• Develop scripts and automated workflows to streamline extraction processes.
• Adapt extraction systems quickly to new domains, acquiring necessary domain knowledge.

Required profile

• Minimum 5 years of experience in information extraction, NLP, or computational linguistics.
• Proficiency in Python for data analysis and NLP tasks.
• Hands‑on experience with NLP libraries such as spaCy, NLTK, Hugging Face Transformers, or Stanford CoreNLP.
• Demonstrated ability to design annotation schemas and clear extraction guidelines.
• Strong understanding of evaluation metrics (precision, recall, F1) and error analysis.
• Excellent written and verbal communication in English, with the ability to document complex processes.

Required skills

• Python
• spaCy
• NLTK
• Hugging Face Transformers
• Stanford CoreNLP