Senior Applied Scientist, Stores Optimization & ML

Amazon Inc.; Palo Alto (CA); On-site; USD 167,000 - 226,000; Full time

Job summary

Amazon's Stores Economics and Science (SEAS) team seeks an Applied Scientist III to advance global optima in complex marketplaces. You will translate business problems into mathematical frameworks, build large-scale algorithms, and deploy production solutions in partnership with product teams.

You will work with a cross-disciplinary group of scientists and engineers to reduce cost-to-serve, optimize selection, and push the boundaries of ML, NLP, statistics, and optimization at Amazon scale.

Qualifications

• 3+ years building machine learning models for business applications.
• PhD or Master’s degree with 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Lead large-scale science initiatives from research through production and deploy algorithms that impact customers.
• Design and implement machine learning and statistical models and own their production performance.
• Drive scientific agenda by identifying new research opportunities and prioritizing initiatives.
• Collaborate with scientists, engineers, and product teams to prototype, validate, and scale solutions.
• Mentor and coach fellow scientists through code reviews, design reviews, and publications.

Skills

ML modeling

PhD or MS + 6+ yrs experience

Programming in Java/C++/Python

Deep learning experience

Education

PhD or Masters + 6+ yrs applied research

Tools

R

scikit-learn

Spark MLlib

MxNet

TensorFlow

NumPy

SciPy

Job description

Amazon's Stores Economics and Science (SEAS) team seeks an Applied Scientist III to advance global optima in complex marketplaces. You will translate business problems into mathematical frameworks, build large-scale algorithms, and deploy production solutions in partnership with product teams.

You will work with a cross-disciplinary group of scientists and engineers to reduce cost-to-serve, optimize selection, and push the boundaries of ML, NLP, statistics, and optimization at Amazon scale.