Machine Learning Scientist, Core AI

Job summary
Amazon Core AI is a central science team that focuses on solving research-intense business problems by leveraging Machine Learning, Econometrics, Statistics, and Data Science. In Berlin, we primarily work on causal demand modeling to better understand the complex economy of Amazon's network of buyers and sellers. To this end, we develop and implement Bayesian demand models, and research on causal inference techniques that allow for complex non-linear models and scale to Amazon-size datasets. We are looking for a Machine Learning Scientist to contribute to our team's research and development efforts.

The ideal candidate is a motivated individual with strong skills in both, researching novel models and algorithms, and applying scientifically sound techniques to tackle abstract business and science problems. Applicants should have an academic track-record and publications in top-tier conferences and journals, and experience with scalable/distributed data processing solutions, Machine Learning frameworks, and software development tools and languages.



Key job responsibilities
In your role as Machine Learning Scientist you will help solving complex business problems in a data-driven manner using predictive and causal modeling. In close collaboration with other scientists and engineers, you will develop and implement models, prepare and analyze data, and perform experiments that are necessary for parameter estimation and model validation. You are expected to create publication-level documents to share learnings and results, and to work with our business partners to collect and incorporate their feedback and requests.

About the team
Amazon Core AI is a diverse, interdisciplinary team with members from all around the world, located across the whole globe. We value and embrace our differences!

We respect timezone differences. We minimize across-timezone dependencies and foster a document-driven work culture.

We put a high value on work-life balance. It isn't only about how many hours you spend at home or in the office; it's also about flexibility in working hours, work location, and finding the right balance between your work and personal lives.

Basic Qualifications

· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field.
· Recent publications in leading journals or conferences on ML, AI, or Statistics.
· Experience programming in Java, C++, Python or related language.
· Fluency in written and spoken English (German is not required).

Preferred Qualifications

· Excellent written and verbal communication skills.
· Experience with applying ML and data science end-to-end in business context.
· Familiar with ML frameworks and related software such as TensorFlow/PyTorch/MXNet, Spark, Pandas.
· Expertise in probabilistic programming, causal inference, or demand modeling.

Amazon Science (www.amazon.science) gives you insight into the company's approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It's the company's ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.

#scienceemea


Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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