Associate Director, AI Policy and Channel
Bristol Myers Squibb
4 months ago
Remote friendly (Princeton, NJ)
United States
Marketing
Role Overview: Associate Director, Artificial Intelligence, Policy and Channel (AIPC)
Responsibilities
- Design, develop, and deploy scalable end-to-end ML pipelines for Market Access, Pricing, and Value Demonstration.
- Set technical standards (reliability, scalability, maintainability) across CI/CD, Git/GitHub, MLOps, and workflow orchestration.
- Apply advanced modeling (time series forecasting, Monte Carlo simulations, supervised/unsupervised learning, NLP/LLMs) to commercial business problems.
- Automate and scale complex data workflows (e.g., rebates, contracts, government policies) for real-time decision support.
- Own full AI product lifecycle (ideation → requirements → development/deployment → integration → monitoring), plan delivery, and measure post-deployment business impact.
- Lead team, mentor junior staff, foster learning culture, and drive cross-functional adoption with senior stakeholders.
Qualifications
- Required: Bachelor’s degree in a quantitative field.
- Preferred: MS or Ph.D. in CS/computational-related/data science field.
- Experience: 5–7+ years hands-on ML development/deployment; prior technical leadership with measurable outcomes; AI product lifecycle management.
- Strongly preferred: biopharmaceutical/healthcare commercial environment.
Required/Preferred Skills
- Python; ML frameworks (TensorFlow/PyTorch/scikit-learn); time-series/Monte Carlo; applied statistics.
- MLOps/cloud: CI/CD, Git/GitHub, AWS/Azure, Airflow/Dagster; NLP/LLMs (agentic AI preferred).
Benefits (explicit)
- Medical/pharmacy/dental/vision; wellbeing/EAP; 401(k), disability/life, insurance; paid time off (includes flexible time off and holidays per location/role).
Responsibilities
- Design, develop, and deploy scalable end-to-end ML pipelines for Market Access, Pricing, and Value Demonstration.
- Set technical standards (reliability, scalability, maintainability) across CI/CD, Git/GitHub, MLOps, and workflow orchestration.
- Apply advanced modeling (time series forecasting, Monte Carlo simulations, supervised/unsupervised learning, NLP/LLMs) to commercial business problems.
- Automate and scale complex data workflows (e.g., rebates, contracts, government policies) for real-time decision support.
- Own full AI product lifecycle (ideation → requirements → development/deployment → integration → monitoring), plan delivery, and measure post-deployment business impact.
- Lead team, mentor junior staff, foster learning culture, and drive cross-functional adoption with senior stakeholders.
Qualifications
- Required: Bachelor’s degree in a quantitative field.
- Preferred: MS or Ph.D. in CS/computational-related/data science field.
- Experience: 5–7+ years hands-on ML development/deployment; prior technical leadership with measurable outcomes; AI product lifecycle management.
- Strongly preferred: biopharmaceutical/healthcare commercial environment.
Required/Preferred Skills
- Python; ML frameworks (TensorFlow/PyTorch/scikit-learn); time-series/Monte Carlo; applied statistics.
- MLOps/cloud: CI/CD, Git/GitHub, AWS/Azure, Airflow/Dagster; NLP/LLMs (agentic AI preferred).
Benefits (explicit)
- Medical/pharmacy/dental/vision; wellbeing/EAP; 401(k), disability/life, insurance; paid time off (includes flexible time off and holidays per location/role).