Senior Applied Scientist, FinAuto

Amazon is hiring a Senior Applied Scientist, FinAuto in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

Builds AI ●●●● is how Level rates this applied scientist role: the job is building AI systems.
The posting mentions TensorFlow, scikit-learn and Python among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Design, develop, and deploy scalable machine learning models and algorithms to optimize financial transactions and operations.

TensorFlowscikit-learnPythonMachine Learning Frameworks

machine-learningstatistical-modelingpredictive-modelingdata-science

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for FinAuto.
If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.
Major responsibilities

- Use machine learning and analytical techniques to create scalable solutions for business problems

- Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes

- Design, development, evaluate and deploy innovative and highly scalable models for predictive learning

- Research and implement novel machine learning and statistical approaches

- Work closely with software engineering teams to drive real-time model implementations and new feature creations

- Work closely with business owners and operations staff to optimize various business operations

- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation

- Mentor other scientists and engineers in the use of ML techniques

Key job responsibilities
Use machine learning and analytical techniques to create scalable solutions for business problems
Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes
Design, develop, evaluate and deploy, innovative and highly scalable ML models
Work closely with software engineering teams to drive real-time model implementations
Work closely with business partners to identify problems and propose machine learning solutions
Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance
Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production
Leading projects and mentoring other scientists, 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

- 7+ years of building machine learning models for business application experience
- Master's degree, or PhD and 5+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

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.

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.

How we rate this

Senior Applied Scientist, FinAuto at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Applied Scientist, FinAuto is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in IN, KA, Bengaluru.
The job was posted on June 2, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningStatistical ModelingPredictive ModelingData ScienceTensorFlowscikit-learnPythonMachine Learning Frameworks

Also common in applied scientist jobs at this level

LLM Generative AI NLP Reinforcement learning AWS Computer vision

Pay

Typical applied scientist job: $167k

This posting doesn't list pay. Use the typical applied scientist figure when pay comes up. See applied scientist jobs

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where statistical modeling was part of your work. What did you do?
Tell me about a project where predictive modeling was part of your work. What did you do?
Tell me about a project where data science was part of your work. What did you do?
Walk me through how you've used TensorFlow in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Machine learning, Statistical Modeling, Predictive Modeling, Data Science, and TensorFlow. 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.

Get your CV reviewed before you apply

Send your CV and the role you want next. Your review arrives by email within 3 days.

Get a free CV review Check your resume with the ATS resume checker