Amazon Sr Applied Scientist Worldwide Amazon Stores Finance Technology 

United States, Washington, Seattle 

138046228

Key job responsibilities
We are seeking for an experienced Applied scientist to lead LLM based development and data analytics and assist in decisions made by Amazon Finance users. In a fast-paced and ambiguous environment, you will perform multiple large, complex, and business critical analyses that will inform product design and business priorities. You will design and build AI based science solutions to transform the analytics landscape.
Keeping a department-wide view, you will focus on the highest priorities and constantly look for scale and automation, while making technical trade-offs between short term and long-term needs. With your drive to deliver results, you will quickly analyze data and understand the current business challenges to assess the feasibility of different science projects as well as help shape the analytics roadmap of the Data Science and Analytics team. Your desire to learn and be curious will help us look around corners for improvement opportunities and more efficient metrics development.
In this role, you will partner with data engineers, business intelligence engineers, product managers, software engineers, and other data scientists.A day in the life
You are a Applied Scientist with an expertise in Machine learning and statistical models. You are comfortable with a higher degree of ambiguity, knows when and how to be scrappy, build quick prototypes and proofs of concepts, innate ability to see around corners and know what is coming, define a long-term science vision, and relish the idea of solving problems that haven’t been solved at scale. As part of our journey to learn about our data, some opportunities may be a dead end and you will balancing unknowns with delivering results for our customers. Along the way, you’ll learn a ton, have fun and make a positive impact at scale.
Seattle, WA, USA

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.