Forecasting AI Manager: Analytical ML & Predictive Solutions

Biopharma Careers; United States; On-site; USD 96,000 - 116,000; Full time

Benefits offered by this job

Health Coverage

Wellbeing Programs

401(k) and financial protection

Family/leave benefits

Job summary

Bristol Myers Squibb in Princeton, NJ is seeking a Manager for Analytical AI Forecasting and Predictive Solutions. You will develop and support advanced forecasting solutions focused on Commercial Demand, partnering with Finance, Commercial, Market Access, and Analytics teams to translate business questions into analytical forecasts.

The role emphasizes hands‑on delivery, technical depth, and cross‑functional collaboration, with opportunities for growth and impact across forecasting use cases.

Qualifications

• BA/BS in quantitative field required; MBA or grad degree preferred.
• Proficiency in Python/R, SQL, Tableau; Git and cloud environments (AWS/Azure) a plus.
• Hands-on analytics and data science experience in forecasting.
• Experience with pharmaceutical forecasting is preferred.

Responsibilities

• Contribute as part of a collaborative team of data scientists, forecasting SMEs, and ML practitioners.
• Develop, maintain, and analyze forecasting models using statistical and ML techniques.
• Translate business questions into analytical forecasting solutions and communicate results to stakeholders.

Skills

Python

R

SQL

Tableau

Git

Cloud (AWS/Azure)

Education

BA/BS in quantitative field

MBA or graduate degree preferred

Tools

Python

R

SQL

Tableau

Git

AWS

Azure

Job description

Bristol Myers Squibb in Princeton, NJ is seeking a Manager for Analytical AI Forecasting and Predictive Solutions. You will develop and support advanced forecasting solutions focused on Commercial Demand, partnering with Finance, Commercial, Market Access, and Analytics teams to translate business questions into analytical forecasts.

The role emphasizes hands‑on delivery, technical depth, and cross‑functional collaboration, with opportunities for growth and impact across forecasting use cases.