Description

Can a large language model read a regulatory change and draft the requirements and control tests that follow from it, accurately enough for a Compliance Officer to sign off? How do you train a breach-risk model when confirmed breaches are rare, arrive months after the event, and mean different things to Compliance, Assurance, and the regulator? What does a model have to prove before a Compliance team acts on its output?

We are looking for an Applied Scientist to join the Data and Analytics team within Risk and Compliance Solutions (RCS). Our team builds the data, analytics, and modeling layer that RCS runs on, from regulatory reports and filings to the intelligence that tells Compliance Officers and our first line of defense (1LoD) partners where risk concentrates and which controls hold. You build the machine learning (ML) and generative artificial intelligence (GenAI) systems in that layer, take them into production, and own the evaluation science that lets Compliance rely on them.

The work spans 3 areas:



risk models that score which open risks and control weaknesses convert to breaches; GenAI systems that remove manual effort from requirement translation, control testing, and regulatory reporting, with human approval gates at every stage; and the evaluation science behind every model and agent the team ships. Financial crime compliance is the first domain, and its constraints shape the science: threats change faster than control sets adapt, and every output faces internal audit and external examination. Once an approach proves out, you carry it into the next compliance domain across the RCS portfolio.

You own problems from formulation to production: framing the science question with Compliance and 1LoD partners, designing experiments and backtests, building and validating models, and shipping them into the pipelines, reports, and tools that RCS teams use. The stack includes Amazon SageMaker, Amazon Bedrock, Amazon Redshift, and AWS Lambda, and you

📌 Applied Scientist II, Risk and Compliance Solutions (Bengaluru)
🏢 Amazon
📍 Bengaluru