Applied Scientist, FinAuto

Amazon Inc.; Bengaluru; On-site; INR 2,000,000 - 4,000,000; Full time

Job summary

Amazon Bengaluru is seeking a Machine Learning Scientist to build scalable financial transaction systems. You will mine billions in data, apply ML/statistics, and help detect anomalies, fraud, and abuse across marketplaces and payments.

You will collaborate with engineers and business teams to deploy models in production, mentor peers, and push the boundaries of data-driven financial controls across a cloud-first platform.

Qualifications

• Experience programming in Java, C++, Python or related language.
• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse.

Responsibilities

• Understand the business and discover actionable insights from large volumes of data through machine learning, statistics or causal inference.
• Analyse and extract information from Amazon's historical transactions data to automate and optimise key processes.
• Research, develop and implement novel ML and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection.
• Use ML and analytical techniques to create scalable solutions for business problems.
• Identify new areas where ML can be applied to solve business problems.
• Partner with developers and business teams to productionize models.
• Mentor other scientists and engineers in the use of ML techniques.

Skills

Java

C++

Python

SQL

RDBMS

Job description

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.

Basic Qualifications

• - Experience programming in Java, C++, Python or related language
• - Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

Preferred Qualifications

• - Experience implementing algorithms using both toolkits and self-developed code
• - Have publications at top-tier peer-reviewed conferences or journals

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.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.