Sr. Applied Scientist, AppStar Data Analytics & Engineering

Amazon is hiring a Sr. Applied Scientist, AppStar Data Analytics & Engineering in New York, United States. It pays $184k-$249k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
The listed pay starts 10% above the typical applied scientist posting on Level.
Tools and skills the posting cites include TensorFlow, scikit-learn and SageMaker.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Lead the invention and delivery of ML-driven systems and graph-based models to identify and mitigate application security risks.

TensorFlowscikit-learnSageMakerPythonAWSS3GlueNeptune

machine-learningapplied-sciencegraph-databasesdata-sciencerisk-modelingsecurity

Are you passionate about using science to make the digital world more secure? The AppStar Data Analytics & Engineering (DNA) team within Amazon's Application Security organization is looking for an Applied Scientist III to invent and build ML-driven systems that fundamentally change how Amazon identifies, prioritizes, and mitigates application security risk at scale.

Our team sits at the intersection of data science, machine learning, and security operations. We build the intelligence layer that powers Amazon's application security programs: risk-scoring models that rank tens of thousands of applications, graph-based systems that map security context across architectures, and analytics platforms that drive data-informed decisions for security leadership. This is science with direct, measurable impact on Amazon's security posture.

As an Applied Scientist III, you will lead the invention and delivery of novel ML solutions for complex, ambiguous problems in the security domain. You will work with large-scale datasets spanning application metadata, code signals, vulnerability findings, and organizational context to develop models that help Amazon focus security resources where they matter most.

Key job responsibilities
- Lead the design, development, and deployment of ML models and scientific solutions for application security prioritization, complexity scoring, and risk assessment

- Frame ambiguous security problems into well-defined scientific challenges, proposing novel approaches when existing methodologies are insufficient

- Architect and implement production-grade ML pipelines (feature extraction, model training, scoring, deployment) on AWS services (S3, Glue, SageMaker, Neptune)

- Develop and extend graph-based models that capture security-relevant relationships between applications, services, teams, and vulnerabilities

- Drive the team's scientific agenda by proposing new research initiatives, conducting experiments, and iterating on models using rigorous evaluation methodologies

- Partner with security engineers, data engineers, and TPMs to translate model outputs into actionable intelligence for security review programs

- Establish and raise the bar for scientific rigor: peer review code and designs, set best practices for experimentation, and document findings for reproducibility

- Publish results internally and externally at peer-reviewed venues when appropriate

About the team
The Data Analytics & Engineering (DNA) team is a small, high-impact group within Amazon's Application Security organization. We build ML models, graph-based systems, and analytics platforms that determine how Amazon prioritizes security coverage across tens of thousands of applications. We're a hybrid team of scientists, data engineers, and security engineers who ship production science, embrace ambiguity, and operate with high ownership. If you want meaningful work that protects customers at Amazon's scale, this is the team.

Diverse Experiences
Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why Amazon Security?
At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.

Inclusive Team Culture
In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.

Training & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.

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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Basic qualifications

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ 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.

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, NY, New York - 183,800.00 - 248,700.00 USD annually

How we rate this

Sr. Applied Scientist, AppStar Data Analytics & Engineering 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

Sr. Applied Scientist, AppStar Data Analytics & Engineering is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $184k-$249k a year.
The role is based in US, NY, New York.
The job was posted on August 10, 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 learningApplied ScienceGraph DatabasesData ScienceRisk ModelingSecurityTensorFlowscikit-learn

Also common in applied scientist jobs at this level

LLM Generative AI NLP Reinforcement learning Computer vision PyTorch

Pay

This job starts at: $184k
Typical applied scientist job: $167k

This posting starts 10% above the typical applied scientist job. 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 applied science was part of your work. What did you do?
Tell me about a project where graph databases 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?
Tell me about a project where risk modeling was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Machine learning, Applied Science, Graph Databases, Data Science, and Risk Modeling. 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.

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