Sr. Applied Scientist, Digital Acceleration

$150,400 - $260,000/Yr

Amazon - Bellevue, WA

Full-time - Mid Level

Bellevue, WA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Applied Scientist role within the Digital Discovery team at Amazon focuses on developing and deploying machine learning algorithms to enhance the discoverability and engagement of digital products and subscriptions. This position involves leveraging expertise in machine learning and deep learning to build predictive models that drive customer acquisition and engagement across various digital offerings, including eBooks, Music, Audible, and Prime. The role requires collaboration with engineering teams and involves the end-to-end lifecycle of ML models, from architecture and training to production deployment, with a strong emphasis on data-driven solutions and rigorous testing.

Responsibilities

• Convert business problems in digital discovery into scientific problems to improve recommendations.
• Collaborate with Data Engineering and BI teams to identify features and build data pipelines.
• Utilize and enhance ML Ops tools for training, validating, deploying, and comparing models with automatic retraining.
• Explain model performance to technical and business leaders.
• Collaborate with the scientific community to present, review, and publish model reports and papers.
• Mentor junior scientists.

Requirements

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

Nice-to-haves

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, TensorFlow, numpy, scipy.
• Experience with large-scale distributed systems like Hadoop and Spark.
• Proven track record of developing and deploying cutting-edge AI/ML models to solve complex real-world problems.
• Strong coding skills in Python and familiarity with popular ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Excellent problem-solving and communication abilities.

Benefits

• Competitive salary based on market location and experience.
• Equity and sign-on payments as part of total compensation package.
• Full range of medical, financial, and other benefits.