AI-Driven Clinical Analytics Lead

Bristol-Myers Squibb Co; Princeton (NJ); On-site; USD 152,000 - 184,000; Full time

Job summary

Bristol Myers Squibb seeks a Senior Manager, Analytical AI in Clinical Development to design and deploy ML pipelines for optimizing clinical trial operations. You will collaborate with IT, medical, biostatistics, and development teams to translate model results into actionable strategies for clinical operations.

The role emphasizes end-to-end AI product lifecycle management, real-time decision support, and cloud-based MLOps, with focus on NLP and real-world data to drive efficiency and improve

Qualifications

• Education in quantitative field (BA/BS) required.
• MBA/MS/PhD in relevant field preferred for advanced roles.
• 3+ years building and deploying ML pipelines in a business setting.
• Proven impact through AI and advanced analytics.

Responsibilities

• Design and deploy end-to-end ML pipelines for clinical study design and execution.
• Automate workflows to analyze protocols, real-world data, and recruitment data.
• Lead cross-functional engagement to align AI solutions with business priorities.
• Oversee AI product lifecycle from ideation to monitoring and improvement.
• Stay ahead of AI trends, integrating NLP and predictive analytics into workflows.

Skills

Machine learning pipelines

Python

SQL

CI/CD

MLOps

NLP

RWD data

Time series forecasting

Monte Carlo simulations

Big data tooling

Education

BA/BS in quantitative field

Advanced degree preferred

Tools

TensorFlow

PyTorch

scikit-learn

Airflow

Dagster

Git/GitHub

Job description

Bristol Myers Squibb seeks a Senior Manager, Analytical AI in Clinical Development to design and deploy ML pipelines for optimizing clinical trial operations. You will collaborate with IT, medical, biostatistics, and development teams to translate model results into actionable strategies for clinical operations.

The role emphasizes end-to-end AI product lifecycle management, real-time decision support, and cloud-based MLOps, with focus on NLP and real-world data to drive efficiency and improve