AI Data Scientist II — Pharma Data & ML Lead

AbbVie

North Chicago (IL)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

AbbVie is seeking an experienced AI Data Scientist II to join the FAiM Team, combining machine learning with clinical science to accelerate drug discovery and improve patient outcomes.

You will design AI-driven solutions, build backend pipelines with FastAPI, and develop automations while collaborating with clinical scientists, IT, and business stakeholders to deliver timely, precise results.

Qualifications

  • Bachelor’s or Master’s degree in a technical field with AI/ML experience
  • Experience applying AI/ML in clinical or pharmaceutical contexts
  • Hands-on with large language models and ML algorithms
  • Strong Python programming with data science libraries
  • Backend development experience using FastAPI
  • Experience building applications on AWS ECS
  • Excellent written and verbal communication; ability to manage multiple projects

Responsibilities

  • Design, develop, and deploy AI-driven solutions for clinical and pharmaceutical challenges
  • Develop and maintain backend data pipelines using FastAPI
  • Create automations using Robotic Process Automation
  • Collaborate with clinical scientists, IT, and business stakeholders
  • Lead multiple projects with high quality standards
  • Translate complex concepts for non-technical stakeholders
  • Engage with internal teams and external vendors on AI trends

Skills

AI/ML in clinical contexts
Python
Large language models
Project management
Communication skills
Backend development

Education

Bachelor’s degree in CS/Data Science or related
Master’s degree

Tools

FastAPI
AWS ECS
Knowledge Graphs

Job description

AbbVie is seeking an experienced AI Data Scientist II to join the FAiM Team, combining machine learning with clinical science to accelerate drug discovery and improve patient outcomes.

You will design AI-driven solutions, build backend pipelines with FastAPI, and develop automations while collaborating with clinical scientists, IT, and business stakeholders to deliver timely, precise results.

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