DESCRIPTION

Are you interested in changing the way accounting and finance works at Amazon? We are a science and engineering team leveraging ML models and GenAI/LLMs to solve real-world problems faced by accountants and financial analysts.
We are part of the Amazon Financials Foundation Services (AFFS) organization. AFFS is responsible for processing and managing billions of financially relevant transactions sent globally from across Amazon each day, including orders, shipments, payments, and inventory movements. AFFS is at the center of Amazon’s key initiatives and fuels the growth of Amazon’s businesses worldwide by ensuring that businesses can easily integrate with our services and that accountants and financial analysts have the right tools to use our data.

As an Sr. Applied Scientist, you’ll work alongside domain experts, engineers, and other scientists to understand business problems, propose scientific solutions, and deploy them to production. You’ll work on scientific initiatives for accelerating reconciliation, standardization, and onboarding. This includes:

• Leveraging GenAI/LLMs to build agentic solutions to accelerate accounting-related research/tasks and produce proactive insights.
• Building AI trust and safety in the financial domain.
• Establishing scalable, efficient, automated processes for large-scale data analysis, machine learning model development, model validation, and serving.
• Developing training/evaluation datasets for model fine-tuning.
• Collaborating with engineering to productionalize research.
• Defining the science direction of the organization and influencing/interacting with senior leadership across Amazon.
• Mentoring and growing scientists within the team.

Specific examples of this work include developing anomaly detection models to identify deviations in payments, building multi-agent systems to perform financial research or onboard new businesses, and fine-tuning LLMs to provide recommendations on next steps.
As an interdisciplinary team, we maintain a balance between scientific research and productionalization. This means, you’ll get a unique opportunity to influence the global scientific community by publishing papers externally and internally while also seeing your work used across Amazon.
You will need to have a start-up like mindset, as you will be working an in a highly iterative and collaborative environment with SDEs, Product Managers, and Accounting stakeholders to propose ideas, experiment, and scale rapidly. You should have a keen eye for what a good user experience should look like, possess excellent written and verbal communication, and have a keen interest in learning about accounting and financial processes.

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 an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
  Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
  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

• Leveraging GenAI/LLMs to build agentic solutions to accelerate accounting-related research/tasks and produce proactive insights.
• Building AI trust and safety in the financial domain.
• Establishing scalable, efficient, automated processes for large-scale data analysis, machine learning model development, model validation, and serving.
• Developing training/evaluation datasets for model fine-tuning.
• Collaborating with engineering to productionalize research.
• Defining the science direction of the organization and influencing/interacting with senior leadership across Amazon.
• Mentoring and growing scientists within the team