Information Extraction Specialist

About the role

The Information Extraction Specialist will design and operate pipelines that transform unstructured and semi‑structured data into structured, actionable datasets. This remote position requires deep expertise in NLP, machine learning, and rule‑based systems to serve diverse domains such as legal, medical, financial, and technical documentation.

Key responsibilities

• Design and implement extraction pipelines for varied document types, including contracts, medical records, financial reports, news articles, and technical manuals.
• 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; analyse errors and iterate on guidelines, data, or model architecture.
• Assess, select, and integrate open‑source or commercial extraction tools and platforms.
• Develop scripts and automated workflows to streamline the extraction process.
• Adapt extraction systems to new domains quickly by acquiring domain knowledge and crafting accurate guidelines.

Required profile

• Minimum 5 years of experience in information extraction, NLP, or computational linguistics.
• Strong written and verbal communication skills in English, with the ability to document complex guidelines clearly.
• Proven ability to design annotation schemas and handle ambiguous extraction cases.
• Deep understanding of evaluation methodologies for extraction tasks.
• Excellent problem‑solving skills to diagnose model errors and propose data‑driven improvements.

Required skills

• Python programming for data analysis and NLP tasks.
• Experience with NLP libraries such as spaCy, NLTK, Hugging Face Transformers, and Stanford CoreNLP.
• Designing annotation schemas and guidelines for complex extraction tasks.
• Calculating and interpreting precision, recall, and F1 metrics.