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Manager, Applied Science
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PhD in Computer Science, AI, Mathematics, or Statistics with specialization in ML (alternatively, MSc. and 5+ years in a ML scientist role).
Deep knowledge of fundamentals, and the state-of-the art, in relevant areas of ML.
2+ years managing a team of applied or data scientists
Strong coding skills in Python.
Strong verbal and written communication skills.
Job summary
Are you interested in building state-of-the-art machine learning systems for the most complex, and fastest growing, transportation network in the world? If so, Amazon has the most exciting, and never-before-seen, challenges at this scale (including those in sustainability, e.g. how to reach net zero carbon by 2040).
Amazon’s transportation systems get millions of packages to customers worldwide faster and cheaper while providing world class customer experience - from online checkout, to shipment planning, fulfillment, and delivery. Our software systems include services that use tens of thousands of signals every second to make business decisions impacting billions of dollars a year, that integrate with a network of small and large carriers worldwide, that manage business rules for millions of unique products, and that improve experience of over hundreds of millions of online shoppers.
We are looking for a Manager, Applied Science (Machine Learning) with a strong academic background and industry experience in the areas of probabilistic machine learning, time series forecasting, and/or anomaly detection.
At Amazon, we strive to continue being the most customer-centric company on earth. To stay there and continue improving, we need exceptionally talented, bright, and driven people. If you'd like to help us build the place to find and buy anything online, and deliver in the most efficient and greenest way possible, this is your chance to make history.
**3+ years of experience, and strong expertise, in any of**: Probabilistic Machine Learning, time series forecasting, anomaly detection.
Experience with cloud computing services such as AWS.
Experience with programming languages such as Java, Scala, and/or others.
Experience working effectively with research science, data engineering, and software engineering teams.
Strong publication/scientific track record.