Sr. Applied Scientist, AppStar Data Analytics & Engineering

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
• [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
• [https://amazon.jobs/en/benefits].
• USA, NY, New York - 183,800.00 - 248,700.00 USD annually