Sr. Applied Scientist, AppStar Data Analytics & Engineering
About the role
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. This team sits at the intersection of data science, machine learning, and security operations, building 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.
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.
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.
Pay
Base salary range: $183,800.00 - $248,700.00 USD annually in New York, NY. 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.
Benefits
- 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
- Parental leave