AI-Driven Data Scientist, Document Automation

ABBVIE; North Chicago (IL); Vor Ort; USD 66.000 - 126.000; Vollzeit

Benefits dieser Stelle

Health benefits

401(k) plan

Paid time off

Zusammenfassung

AbbVie in the United States is seeking a data/AI-focused professional to transform document management across regulatory, quality, and scientific teams. You will design and deploy AI-enabled workflows for automated content authoring, summarization, metadata extraction, and compliance reviews, interfacing with data pipelines and enterprise systems.

The role sits at the intersection of data science, software engineering, and business processes, applying LLMs, RAG, and modern AI tools to speed

Qualifikationen

• Bachelor's degree in Computer Science, Data Science, or related field.
• Experience developing production-grade data, analytics, or AI applications.
• Knowledge of modern AI technologies (LLMs, RAG) and APIs.

Aufgaben

• Partner with regulatory, quality, and scientific teams to identify AI-driven process improvements.
• Design, develop, and deploy AI-enabled content authoring, summarization, and metadata extraction solutions.
• Build data pipelines, integrations, and knowledge management frameworks connecting repositories and AI services.
• Develop ML/AI solutions including LLMs, RAG, and AI agents to improve document lifecycle management.
• Create scalable tools and intuitive interfaces to enable business users to leverage AI capabilities.
• Evaluate emerging technologies and recommend practical, scalable implementations.

Kenntnisse

Python

AI/ML

Data pipelines

APIs

Ausbildung

Bachelor's degree in Computer Science or related field

Tools

AWS

Azure

GCP

Document management systems

Jobbeschreibung

AbbVie in the United States is seeking a data/AI-focused professional to transform document management across regulatory, quality, and scientific teams. You will design and deploy AI-enabled workflows for automated content authoring, summarization, metadata extraction, and compliance reviews, interfacing with data pipelines and enterprise systems.

The role sits at the intersection of data science, software engineering, and business processes, applying LLMs, RAG, and modern AI tools to speed