Applied Scientist II, FinAuto
Amazon· Applied Science
About this role
Interested to build the next generation Financial systems that can handle billions of dollars in transactions? Interested to build highly scalable next generation systems that could utilize Amazon Cloud?
Massive data volume + complex business rules in a highly distributed and service oriented architecture, a world class information collection and delivery challenge. Our challenge is to deliver the software systems which accurately capture, process, and report on the huge volume of financial transactions that are generated each day as millions of customers make purchases, as thousands of Vendors and Partners are paid, as inventory moves in and out of warehouses, as commissions are calculated, and as taxes are collected in hundreds of jurisdictions worldwide.
Key job responsibilities
• Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference.
• Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes
• Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection.
• Use machine learning and analytical techniques to create scalable solutions for business problems.
• Identify new areas where machine learning can be applied for solving business problems.
• Partner with developers and business teams to put your models in production.
• Mentor other scientists and engineers in the use of ML techniques.
A day in the life
• Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference.
• Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes
• Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection.
• Use machine learning and analytical techniques to create scalable solutions for business problems.
• Identify new areas where machine learning can be applied for solving business problems.
• Partner with developers and business teams to put your models in production.
• Mentor other scientists and engineers in the use of ML techniques.
About the team
The FinAuto TFAW(theft, fraud, abuse, waste) team is part of FGBS Org and focuses on building applications utilizing machine learning models to identify and prevent theft, fraud, abusive and wasteful(TFAW) financial transactions across Amazon. Our mission is to prevent every single TFAW transaction. As a Machine Learning Scientist in the team, you will be driving the TFAW Sciences roadmap, conduct research to develop state-of-the-art solutions through a combination of data mining, statistical and machine learning techniques, and coordinate with Engineering team to put these models into production. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.
Massive data volume + complex business rules in a highly distributed and service oriented architecture, a world class information collection and delivery challenge. Our challenge is to deliver the software systems which accurately capture, process, and report on the huge volume of financial transactions that are generated each day as millions of customers make purchases, as thousands of Vendors and Partners are paid, as inventory moves in and out of warehouses, as commissions are calculated, and as taxes are collected in hundreds of jurisdictions worldwide.
Key job responsibilities
• Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference.
• Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes
• Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection.
• Use machine learning and analytical techniques to create scalable solutions for business problems.
• Identify new areas where machine learning can be applied for solving business problems.
• Partner with developers and business teams to put your models in production.
• Mentor other scientists and engineers in the use of ML techniques.
A day in the life
• Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference.
• Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes
• Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection.
• Use machine learning and analytical techniques to create scalable solutions for business problems.
• Identify new areas where machine learning can be applied for solving business problems.
• Partner with developers and business teams to put your models in production.
• Mentor other scientists and engineers in the use of ML techniques.
About the team
The FinAuto TFAW(theft, fraud, abuse, waste) team is part of FGBS Org and focuses on building applications utilizing machine learning models to identify and prevent theft, fraud, abusive and wasteful(TFAW) financial transactions across Amazon. Our mission is to prevent every single TFAW transaction. As a Machine Learning Scientist in the team, you will be driving the TFAW Sciences roadmap, conduct research to develop state-of-the-art solutions through a combination of data mining, statistical and machine learning techniques, and coordinate with Engineering team to put these models into production. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.
Basic qualifications
- PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred qualifications
- Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms
- Experience in professional software development
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.
Frequently Asked Questions
Is the salary disclosed for the Applied Scientist II, FinAuto position at Amazon?
The salary for this Applied Scientist II, FinAuto role at Amazon is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Applied Scientist II, FinAuto position at Amazon located?
This Applied Scientist II, FinAuto role at Amazon is based in Bengaluru, Karnataka, IND. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Applied Scientist II, FinAuto role at Amazon full-time or part-time?
This is listed as a full time position. It is posted as a Applied Scientist II, FinAuto role in the Applied Science department at Amazon.
Which team or department does the Applied Scientist II, FinAuto at Amazon belong to?
This Applied Scientist II, FinAuto position is part of the Applied Science department at Amazon. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Applied Scientist II, FinAuto position at Amazon?
Click the "Apply Now" button on this page. You will be redirected to Amazon's official application portal hosted on amazonjobs where you can submit your application directly.
When was the Applied Scientist II, FinAuto job at Amazon posted?
This Applied Scientist II, FinAuto position at Amazon was posted on Jun 18, 2026. Apply as soon as possible — early applications are often reviewed first.
Applied Scientist II, FinAuto
Amazon
You'll be redirected to Amazon's official application page on amazonjobs.