Associate Scientist, Data II

AbbVie•North Chicago, IL

7h•$65,500 - $125,500

About The Position

The doc management team is focused on transforming how pharmaceutical content is created, managed, reviewed, and delivered across the organization. This role will help accelerate the adoption of AI, automation, and modern data technologies to improve document authoring, quality control, knowledge management, and operational efficiency. The successful candidate will work at the intersection of data science, software engineering, and scientific business processes to develop intelligent solutions that streamline document-centric workflows. This includes leveraging large language models (LLMs), machine learning, knowledge management technologies, and system integrations to enable more efficient content creation, review, compliance, and reuse. The role will serve as a key partner in helping teams adapt emerging technologies and integrate them into everyday ways of working.

Requirements

Bachelor's degree in Computer Science, Data Science, Software Engineering, or a related quantitative field required.
Strong programming skills in Python and experience developing production-grade data, analytics, or AI applications.
Experience designing data architectures, APIs, database solutions, and cloud-based applications using platforms such as AWS, Azure, or GCP.
Hands-on experience with modern AI technologies, including large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), vector databases, AI agents, and document intelligence solutions.
Strong understanding of software engineering principles, system integration, data governance, and scalable application development.

Nice To Haves

Relevant industry experience in pharmaceutical, biotechnology, content management, or AI-enabled digital transformation initiatives are preferred.
Experience working with enterprise content management systems, document repositories, knowledge management platforms, or workflow automation technologies is highly desirable.
Familiarity with pharmaceutical, biotechnology, regulatory, clinical, quality, or scientific documentation processes is preferred.
Experience developing dashboards, visualization tools, and intuitive user experiences that drive adoption of new technologies

Responsibilities

Partner with document management, regulatory, quality, and scientific teams to identify opportunities for AI-driven process improvement and workflow automation.
Design, develop, and deploy solutions that support automated content authoring, content reuse, document summarization, metadata extraction, quality control, and compliance-related reviews.
Build and maintain data pipelines, integrations, APIs, and knowledge management frameworks that connect document repositories, enterprise systems, and AI services.
Develop and apply machine learning and generative AI solutions, including large language models (LLMs), retrieval-augmented generation (RAG), agentic workflows, and other modern AI technologies to improve document lifecycle management.
Create scalable tools, applications, and user interfaces that enable business users to effectively leverage AI and automation capabilities.
Evaluate emerging technologies and recommend practical solutions that can be adopted across the organization to increase productivity and operational effectiveness.
Collaborate with business stakeholders to translate requirements into technical solutions while ensuring alignment with regulatory, quality, security, and governance standards.
Establish best practices, training materials, and change management approaches that help teams successfully adopt new digital capabilities.
Communicate technical concepts and project outcomes to both technical and non-technical audiences, driving understanding and adoption across diverse stakeholder groups.