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Salary

Not Disclosed

Location

Banglore

Highlights

Leverage cutting-edge ML for financial fraud detection, mentor other scientists, operationalize scalable models.

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Description

As a Machine Learning Scientist in the FinAuto TFAW team at Amazon, you will play a pivotal role in driving our mission to prevent every single theft, fraud, abusive and wasteful (TFAW) financial transaction. You will leverage your expertise in machine learning, statistics, and causal inference to derive actionable insights from vast amounts of historical transactions data.

Your responsibilities include researching, developing, and implementing novel approaches for detecting anomalies, theft, fraud, abuse, and wasteful activities through a combination of data mining, statistical techniques, and cutting-edge machine learning models. You will work closely with the engineering team to ensure your solutions are operationalized at scale, thereby automating and optimizing key business processes.

Partnering with cross-functional teams, you will identify new areas where machine learning can be applied to solve complex business problems. Additionally, you will mentor fellow scientists and engineers in the application of advanced ML techniques, fostering a collaborative environment that drives innovation and excellence.

Join us at Amazon FGBS Org’s FinAuto TFAW team and help shape the future of financial transaction analysis using state-of-the-art machine learning solutions.

Skills

Machine-learning Statistical-inference Data-mining Python-programming SQL