Data Scientists (all levels), Amazon Consumer Analytics
This is one of the most exciting machine learning job opportunities today. If you have deep machine learning knowledge, know how to deliver highly innovative solutions to challenging problems, we want to talk to you.
Location: Seattle, WA
Hundreds of millions of customers, millions of products, billions of purchase transactions, petabytes of complete clickstream history... Stop playing in sand boxes! Join us to enjoy the world's richest collection of e-commerce and in-device data to segment and target customers on site and through email, social, mobile and display - not to mention the gorgeous correlations (median AUC of ~0.85 over a thousand models).
Amazon Consumer Analytics team is looking for Data Scientists at all levels.
You will work with distributed machine learning and statistical algorithms across multiple platforms (AWS, Hadoop and the data warehouse) to harness enormous volumes of online data at scale to match customers and products/offers based on probabilistic reasoning. The Data Scientist will be a technical player in a team working to develop ultrascale platforms for machine learning, and help develop new, revolutionary approaches that optimize Amazon's systems using cutting edge quantitative techniques. You need to be fluid in:
- Data warehousing and Hadoop (SQL, Hive, Pig).
- Feature extraction, feature engineering and feature selection.
- Machine learning, statistical algorithms and recommenders.
- Model evaluation, validation and deployment.
- Experimental design and testing.
We write custom data extractors, target builders, score optimizers, model managers for Hadoop. This is one of the most exciting machine learning job opportunities on the internet today. If you have a deep technical knowhow in machine learning, know how to deliver highly innovative solutions to challenging problems that directly impact the company's bottom-line; we want to talk to you.
- A PhD in machine learning, engineering, statistics, physics or a highly quantitative field. Masters with equivalent experience will be considered.
- Proven ability to relate to and solve business problems through machine learning and statistics.
- 3+ years of hands-on experience developing and implementing machine learning algorithms and/or statistical models.
- Programming, prototyping and scripting skills (Oracle, SQL, Hive, Pig, SAS, R, Weka, Python).
- Communication and data presentation skills.
- A strong track record of innovating through machine learning and statistical algorithms and their applications.
- Strong demonstrated skills implementing and deploying large scale machine learning applications and tools.
- Strong skills and experience with programming in SQL, Hive, Pig, R, SAS macros and familiarity/experience with AWS.
- 3 years of post-PhD experience.
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