Data scientist

This is a Data Scientist role in Merck’s S&T Data Science & Biostatistics team focused on applying advanced statistics and modern data science to global animal health manufacturing. You will lead end-to-end projects spanning quality control, yield optimization, maintenance, deviation management, and regulatory submissions.

• Lead end-to-end data science and statistical projects (DOE, SPC, regression, GLMs, multivariate analysis, optimization, simulation, predictive modeling, machine learning)
• Assess data quality and maintain metadata awareness and prepare reports for stakeholders and regulatory submissions
• Develop reproducible, well-documented code and data science pipelines
• Automate repeatable tasks and integrate data science into operational workflows
• Communicate complex statistical and modeling results clearly with actionable recommendations

The role emphasizes advanced statistical methods and modeling techniques including DOE, SPC (Statistical Process Control), regression, GLMs (generalized linear models), multivariate analysis, optimization, simulation, predictive modeling, and machine learning. Work includes building reproducible, well-documented code and data science pipelines and integrating analysis into operational workflows.

The ideal candidate is a mid-level data scientist with at least 2 years of hands-on experience in data science, statistics, or biostatistics—preferably in pharmaceutical or manufacturing settings. They can lead end-to-end statistical and machine learning projects using DOE, SPC, regression, GLMs, optimization, simulation, and predictive modeling, while building reproducible, well-documented pipelines and communicating results for regulatory submissions.