Principal Research Data Scientist (Hybrid)

AbbVie•North Chicago, IL

6d•$124,500 - $236,500•Hybrid

About The Position

AbbVie Information Research seeks a Principal Research Data Scientist to design, architect, and develop AI data solutions that drive the advancement of our AI and machine learning ecosystem. In this role, you will collaborate closely with data engineers, data scientists, architects, and business analysts to support world-class research and development, foster technological innovation, and promote continuous improvement.

Requirements

Bachelor's Degree with 8 years’ experience; Master's Degree with 7 years’ experience; PhD with 3 years’ experience.
Must have experience with Neo4j & Elastic Search database technologies.
Must have experience with supporting AI/ML initiatives including LLM integration, Data Agents, Agentic Memory, and Graph RAG systems.
Must have experience with text mining and unstructured data processing.
Must have experience with Pharmaceutical R&D industry-centric datasets.

Nice To Haves

Background in life sciences or work experience in the pharmaceutical industry preferred
Master’s degree preferred

Responsibilities

Collaborate with cross functional team of architects, data scientists, business system analysts, and product owners to understand requirements and deliver fit for purpose solutions.
Design, develop, and maintain scalable AI ready data solutions for diverse data sets to support pharma R&D value chain.
Support projects involving the integration of LLMs (such as GPT or Claude or similar technologies) for data mining, knowledge extraction, and automation of data-driven insights.
Capture and interpret user requirements into expressive data models that enable graph analytics, semantic reasoning, and GenAI integration.
Research and recommend appropriate tools, frameworks, and platforms for graph databases, vector stores, and large language models integration including agent-based solutions.
Provide technical leadership, act as a subject matter expert and advisor to partners on the feasibility and impact of emerging technologies in the AI data space.
Architect solutions to operationalize machine learning models, including model deployment, monitoring, and lifecycle management.
Ensure compliance with applicable AbbVie software development, lifecycle policies, and procedures.
Present complex graphs and GenAI relationships through visualizations, translating technical results into business insights. Create compelling data-driven presentations and dashboards for executives, project sponsors, and non-technical audiences.