Description

　　Amazon Payments Services build systems that process payments at an unprecedented scale, with accuracy, speed, and mission-critical availability. We process millions of transactions every day worldwide across various payment methods for different Amazon businesses. Over 100 million customers and merchants send hundreds of billions of dollars moving at light-speed through our systems annually. PayStation is our abstraction layer which offers a singular authoritative set of payment APIs.

　　We are looking for an entrepreneurial and skilled applied scientist to join the PayStation Intelligence team. As Senior Applied Scientist, you will design quantitative systems and forecasting models that generate multi-billion dollar predictions of the highest level of visibility and importance for Amazon's Payments and Customer Experience. You will work closely with Software Development Engineers to construct models on data at massive scale, and implement software solutions for science problems. You will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, and possesses strong communication skills to effectively interface between technical and business teams. You will collaborate in a fast paced environment with multiple teams (software development, Project Management, Build and Release, etc) to deliver impacting our broad base customers. You will contribute to the research community by working with other scientists across Amazon and our Global Payments Tech organization as well as by collaborating with academic researchers and publishing papers. Finally, you will also have exposure to senior leadership as we communicate results and provide scientific guidance to the business.

　　Key job responsibilities

　　Perform hands-on analysis and modeling of enormous data sets to develop insights for Amazon Payments businesses.

　　Lead the design, implementation, and successful delivery of solutions for scientifically-complex problems and systems in production, which can be brand new, or evolving from existing ones.

　　Lead science reviews for not only your team, also related science or adjacent teams.

　　Run A/B experiments, gather data, and perform statistical analysis,

　　Identify and devise new research solutions following a customer-obsessed scientific approach to address customer or business problems when the problem is ill-defined, needs to be framed, and new methodologies or paradigms need to be invented at the product level

　　Research and explore state-of-the-art and innovative machine learning approaches

　　Recruit Scientists for the team and provide mentorship.

　　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

　　Statistics, Applied Mathematics, Operation Research, Economics or a related quantitative bachelor or master degree.

　　5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, Weka, SAS, Matlab)

　　4+ years of data scientist experience

　　Experience in machine-learning methodologies (e.g., supervised and unsupervised learning, deep learning, etc.)

　　Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data.

　　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.

　　PhD degree in math, statistics, computer science, or related science field.

　　Excellent quantitative modeling, statistical analysis skills and problem-solving skills. Sophisticated user of statistical tools.

　　Experience in Payments domain including payment processing, security requirements and privacy requirements

　　Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

　　Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences

　　Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations

　　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. Applicants should apply via our internal or external career site.