Applied Scientist I, Payments Engineering Team

Key Skills

C Programming, C++, Cloud computing, Data science techniques, Java Programming, Machine learning techniques, MATLAB Programming, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job 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. Over 100 million customers and merchants send hundreds of billions of dollars moving at light-speed through our systems annually. We are looking for a highly skilled, experienced, and motivated Applied Scientist to innovate and solve the challenges at a massive scale.

This Applied Scientist role 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. A successful candidate 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 contribute to the research community by working with other scientists across Amazon and our Payments Engineering as well as by collaborating with academic researchers and publishing papers. You will work closely with Software Development Engineers to invent and construct models on data at massive scale and it is likely that your work will end up in an Amazon product. Finally, you will also have exposure to senior leadership as we communicate results and provide scientific guidance to the business.

As a Applied Scientist you will:

• · Drive collaborative research and creative problem solving.
• Constructively critique peer research and mentor junior scientists and engineers.
• Create experiments and prototype implementations of new learning algorithms and prediction technique.
• Collaborate with engineering teams to design and implement software solutions for science problems.
• Contribute to progress of the Amazon and broader research communities by producing publication
• Effectively collaborate in a fast paced environment with multiple teams in large organization (software development, Project Management, Build and Release, etc).

BASIC QUALIFICATIONS

• Ph.D./M.S. in Computer Science, Machine Learning, Statistics or a related quantitative field
• Hands-on experience in predictive modeling and analysis
• Hands-on experience in Python, Perl, Scala, Java, C#, C++ or other similar languages
• Experience in software development
• Proficiency in model development, model validation and model implementation for large-scale applications
• Significant peer-reviewed scientific contributions in premier journals and conferences

PREFERRED QUALIFICATIONS

• Experience applying ML to solve complex problems in an applied environment
• Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis

Ability to convey mathematical results to non-science stakeholders

• Strength in clarifying and formalizing complex problems
• Experience with defining research and development practices in an applied environment
• Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts

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.