Applied Scientist - Prime Decision Sciences

Job ID: 1218253 | Amazon.com Services LLC

DESCRIPTION

Interested in modeling and understanding customer behavior through machine learning, artificial intelligence, and data mining over TB scale data with huge business impact on millions of customers? Join our team of Scientists and Engineers developing models to predict customer behavior and optimize the customer experience with Amazon Prime. This includes identifying who our customers are and providing them with personalized relevant content. As an ML expert, you will partner directly with product owners to intake, build, and directly apply your modeling solutions.

There are numerous scientific and technical challenges you will get to tackle in this role, such as global scalability of models, combinatorial optimization, cold start problem, accelerated experimentation, short/long term goals modeling, cohort identification in a semi-supervised setting, and multi-step optimization leading to reinforcement learning of the customer journey. We employ techniques from supervised learning, bandits, optimization, and RL.


As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of.

You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Redshift, Sagemaker, DynamoDB, S3, ...), various ML algorithms and techniques (XGBoost, Random Forests, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning), and statistical modeling techniques.

Major responsibilities
· Build and develop machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams.
· Leverage Bandits and Reinforcement Learning for Recommendation Systems.
· Develop offline policy estimation tools and integrate with reporting systems.
· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
· Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes.
· Work closely with the business to understand their problem space, identify the opportunities and formulate the problems.
· Use machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems.
· Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.




BASIC QUALIFICATIONS

· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· 2+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language
· MS or PhD in Computer Science, Machine Learning, Natural Language Processing, Statistics, Computer Vision, Applied Mathematics or in another highly quantitative field.
· Skills with Python, Java, Scala, or other programming language, as well as with R, Matlab or similar scripting language.
· Communication and data presentation skills.
· Ability to distill problem definitions, models, and constraints from informal business requirements, and to deal with ambiguity and competing objectives.
· Experience in developing solutions for real-world applications.

PREFERRED QUALIFICATIONS

· PhD in Machine Learning, Computer Science, Statistics, Physics, Applied Mathematics or other highly quantitative field · Experience handling terabyte size datasets
· Knowledge of relational databases (SQL)
· Experience working with distributed computing
· Strong communication and data presentation skills