Snr Applied Scientist, Tax Engine
DESCRIPTION
Would you like to work on developing ML models for one of the largest transactional distributed systems in the world? How about working with customers and peers from the entire range of Amazon's business and Science on complex real world problems, backed with high volume data ? Whether you're passionate about building highly scalable and reliable systems or a scientist who likes to solve business problems, Amazon Tax Platform Services is the place for you.
We are responsible for the tax calculation platform, providing the core services that calculate taxes (sales tax and VAT) for all Amazon sales, physical and digital, globally. We seek to provide the correct tax amounts to the customer when placing their Amazon order, and ensure all records are stored safely to meet tax law requirements around the globe. Our challenges include staying on top of the complex and ever-changing global tax legislations as well as computing calculations correctly and quickly, thousands of times a second, and each one needs to be accurate.
As an Applied scientist, you will provide machine learning leadership to the team that helps increase the accuracy of Tax classification based product information in Amazon catalogue making it the biggest and most challenging tax classification using Machine learning models globally. You will work with large language models, to build various machine learning models to predict accuracy of human's on specific tasks, reason with large volumes of systems changes to identify causal determinants, apply generative AI to model outcomes from sparse data.
You will help us innovate different ways to enhance tax classification experience for our global customers.
You will need to be entrepreneurial, work in a highly collaborative environment with SDEs, Product managers and businesses. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality.
BASIC QUALIFICATIONS
- 5+ 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 large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
The base salary for this position ranges from $195,900/year up to $327,200/year. Salary is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. Applicants should apply via our internal or external career site.