Senior Manager, Data Science & Production ML

Amazon Inc.; Arlington (VA); On-site; USD 182,000 - 237,000; Full time

Job summary

Amazon.com Services LLC in Arlington, Virginia, seeks a Manager III, Data Science to lead a team delivering production ML and experimentation pipelines. You will research, develop, and deploy production ML models, monitor performance, and analyze business impact to inform product improvements.

Responsibilities include setting the team research roadmap, prioritizing analytics projects, and proposing approaches to solve new business problems.

Qualifications

• PhD or foreign equivalent degree in Computer Science, Mathematics, Statistics, Machine Learning, or a related field and five years of experience in the job offered or a related occupation.
• Employer will accept a master’s degree or foreign equivalent degree in Computer Science, Mathematics, Statistics, Machine Learning, or a related field and seven years of experience in the job offered or a related occupation as equivalent to a PhD and five years of experience.
• Must have five years of experience in programming in Python or R.
• Must have one year of experience in managing scientists or machine learning engineers.

Responsibilities

• Manage a team of data and applied scientists delivering production machine learning (ML) and experimentation pipelines.
• Research, develop, and deploy production ML models.
• Support, monitor, and improve production ML models.
• Perform analysis on business performance and make recommendations to improve products.
• Set team research roadmap and prioritization on a routine basis.
• Propose analytics approaches to solve new business problems.

Skills

Python or R

Managing scientists or ML engineers

Education

PhD in Computer Science/Math/Stats/ML

Master’s degree plus 7 years experience equivalent to PhD

Job description

Amazon.com Services LLC in Arlington, Virginia, seeks a Manager III, Data Science to lead a team delivering production ML and experimentation pipelines. You will research, develop, and deploy production ML models, monitor performance, and analyze business impact to inform product improvements.

Responsibilities include setting the team research roadmap, prioritizing analytics projects, and proposing approaches to solve new business problems.