Pharma AI/ML Lead - Principal Data Scientist

AbbVie; Florham Park (NJ); On-site; USD 140,000 - 190,000; Full time

Job summary

AbbVie seeks a Principal Data Scientist to lead a portfolio of advanced analytics within the APEX Enterprise Advanced Analytics and Innovation team. You will drive end-to-end ML/AI solutions for personalized commercial engagement and performance optimization across multi-source data.

The role requires deep expertise in applied machine learning, statistical modeling, experimentation, and omni-channel analytics in a pharmaceutical context.

Qualifications

• PhD/MD preferred for senior level; strong publication or project track record advantageous.
• 8+ years in data science, ML or analytics with production models.
• Experience in pharmaceutical/biotech commercial analytics preferred.
• Experience productionizing ML in cloud environments and with MLOps.

Responsibilities

• Lead end-to-end analytics portfolio, including model design, validation, deployment and monitoring.
• Translate business requirements into technical specifications for analytics products.
• Develop predictive and inferential models to optimize customer engagement and performance.
• Ensure rigorous methodologies, reproducibility, and documentation across projects.
• Collaborate with product owners, engineering, and platform teams to deliver scalable solutions.
• Stay current with advances in ML, causal inference, and pharma analytics.

Skills

ML & stats

Leadership

Problem translation

DS lifecycle

Software engineering

Pharma data

Communication

AI engineering

Cross-functional

Education

Bachelor's degree in quantitative field

Tools

Python

R

SQL

PyTorch/TensorFlow

Job description

AbbVie seeks a Principal Data Scientist to lead a portfolio of advanced analytics within the APEX Enterprise Advanced Analytics and Innovation team. You will drive end-to-end ML/AI solutions for personalized commercial engagement and performance optimization across multi-source data.

The role requires deep expertise in applied machine learning, statistical modeling, experimentation, and omni-channel analytics in a pharmaceutical context.