Lead Applied Scientist, MAPLE

2 weeks ago


Seattle, Washington, United States Amazon Full time

Job Overview:
At Amazon, we are seeking a passionate and innovative individual to join our team as a Senior Applied Scientist within the MAPLE division. This role focuses on enhancing the shopping experience for our customers through the development of advanced algorithms and state-of-the-art modeling techniques.

Key Responsibilities:
  • Innovate and implement cutting-edge machine learning algorithms.
  • Leverage expertise in supervised learning and causal inference to optimize machine learning outcomes.
  • Scale optimization strategies to generate significant business impact.
  • Design and execute A/B tests, followed by thorough statistical analysis of results.
  • Collaborate with distributed machine learning and statistical methodologies to manage vast datasets effectively.
  • Contribute to the scientific community by presenting and publishing research findings.
  • Provide mentorship to junior engineers and scientists.
  • Engage with various internal stakeholders, including business and engineering teams, to align objectives within your area of focus.
About Our Team:
Our mission is to deliver timely and relevant payment-related recommendations to enhance the shopping experience for Amazon customers. We foster a collaborative culture that emphasizes mutual support and continuous learning. Our team dedicates time each week to personal development and knowledge expansion, aiming to make a substantial impact on both Amazon's business and our customers.

Basic Qualifications:
  • Minimum of 3 years of experience in developing machine learning models for business applications.
  • PhD or Master's degree with at least 6 years of applied research experience.
  • Proficiency in programming languages such as Java, C++, or Python.
  • Familiarity with neural deep learning techniques and machine learning methodologies.
  • Proven track record of publications in machine learning.
Preferred Qualifications:
  • Experience with modeling tools including R, scikit-learn, Spark MLLib, MxNet, TensorFlow, numpy, and scipy.
  • Knowledge of large-scale distributed systems like Hadoop and Spark.
  • Understanding of reinforcement learning concepts.
  • Experience with optimization frameworks.

Amazon is dedicated to fostering a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status.

For individuals with disabilities who require accommodations, please reach out to us.

Our compensation reflects the labor market across various US regions. The base salary for this position ranges from $150,400 to $260,000, depending on the geographic market.

Compensation may include equity, sign-on bonuses, and other forms of remuneration, along with a comprehensive benefits package.



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