Job Information
Amazon Senior Applied Scientist, Amazon Payments in Seattle, Washington
Description
Are you excited about influencing the payment experience of millions of customers worldwide? The moment a customer makes a payment on Amazon is when trust is established – trust that the item is delivered on time, a refund is provided quickly if needed, a digital movie purchased will play immediately, a seller receives their disbursement, and hundreds of other experiences across Amazon when a customer completes a payment. The Payment Acceptance & Experience (PAE) team, within the Amazon Payments organization, has the mission to build the most trusted, intuitive, and accessible payment experience on Earth. Within PAE, the PAE ML team has a mission to enhance customer payments experience that requires advancing the state of the art in machine learning. We work backwards from the customer to create value for them by leveraging an underlying applied science methodology. We deploy our solutions through Native AWS services that operate at Amazon scale. We strive to publish our solutions and share our findings so that the broader Amazon scientific community can benefit.
As an applied scientist on our team, your role is to leverage your strong background in Computer Science and Machine Learning to help build the next generation of our model development and assessment pipeline, harness and explain rich data at Amazon scale, and provide automated insights to improve machine learned solution that impacts Payments experience of millions of customers every day. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. The ideal candidate will have experience with generative machine learning models and applying science to various business contexts. We are particularly interested in experience applying transformer modeling, predictive modeling, natural language processing, deep learning, and reinforcement learning at scale. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.
Your responsibilities include:
. Analyze the data and metrics resulting from traffic into Amazon Payments experiences.
. Design, build, and deploy effective and innovative ML solutions to improve various components of the Amazon Payments experience, using transformers modeling, predictive modeling, recommendations, anomaly detection, ranking, and forecasting.
. Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.
. Publish and present your work at internal and external scientific venues in the fields of genAI/ML/NLP/IR/Forecasting.
Your benefits include:
. Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers.
. The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems.
. Excellent opportunities, and ample support, for career growth, development, and mentorship.
. Competitive compensation, including relocation support.
The PAE Applied Science team operates primarily out of Amazon's Seattle office. We are a new and expanding team where you will have an opportunity to influence our goals and mission. We collaborate with Software Engineering, Data Engineering, Product Management and Marketing teams within Amazon Consumer Payments to solve and deploy machine learning solutions at scale.
Please visit https://www.amazon.science for more information
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
Basic Qualifications
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
Preferred Qualifications
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.
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, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location 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. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.