AmazonPosted 5mo ago

Senior Applied Scientist, FinTelligence

Senior Applied Scientist, FinTelligence at Amazon scores 95 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

US, WA, Bellevueseniorfull-time$167k-$226k

AI in this role

tensorflowscikit-learn

ai-agents

At Amazon's FinTech organization, we are building AI systems that process hundreds of millions of financial transactions, turn complex documents into actionable intelligence, and power autonomous agents that learn from every customer interaction. We are looking for a Senior Applied Scientist to lead the development of generative AI applications that change how finance teams work, tackling problems at the intersection of large language models, multi-agent systems, and real-world financial operations.

Key job responsibilities
What You'll Work On

- Building AI systems that finance teams trust enough to rely on without manual review, where precision isn't a nice-to-have, it's a compliance requirement
- Designing agents that learn from user corrections and get measurably better with every interaction, not just at the next model release
- Solving inference at massive scale using tiered model architectures, intelligent routing, and small language models that deliver production-grade accuracy at a fraction of frontier model cost
- Developing evaluation frameworks that catch quality regressions before customers do and gate every model change before it ships

Who Thrives Here

- You're someone who cares as much about shipping as about research.
- You've built models that run in production, not just in notebooks.
- You're comfortable working across the full stack, from model architecture to deployment to measuring whether the customer's workflow actually changed.

- You operate well in cross-functional settings where science, engineering, and business teams inform each other continuously.
- You'd rather solve a hard real-world problem than optimize a benchmark.

What Makes This Different

Your work ships to production and directly changes how thousands of finance professionals operate daily
The problems are genuinely hard: financial data is messy, regulated, high-stakes, and operates at a scale where naive LLM approaches break down
You'll work across multiple domains — from contract intelligence to cash application to financial data investigation — not a single narrow use case

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.

Basic qualifications

- PhD, or Master's degree and 6+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- Experience with neural deep learning methods and machine learning
- Experience programming in Java, C++, Python or related language

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.
- Have publications at top-tier peer-reviewed conferences or journals

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 range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 167,100.00 - 226,100.00 USD annually

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI AgentsTensorFlowscikit-learn

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through how you've used TensorFlow in your day-to-day work.
What are the limits of scikit-learn that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: AI Agents, TensorFlow, and scikit-learn. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

Want your resume actually rewritten for this job?

The free preview above is everything we have today. A full resume rewrite is not live yet and has no price set. Join the waitlist and we will email you if we open it.