Description
Are you passionate about transforming how Amazon identifies and addresses security risks through data science and machine learning? Does the prospect of using advanced analytics to drive measurable improvements in application security at scale excite you?
As a Data Scientist on the AppStar DNA team (Data & Analytics Engineering), you will build data-driven solutions that help security teams across the AppStar organization identify patterns, prioritize efforts, and measure the impact of security initiatives. You will develop machine learning models, conduct exploratory data analysis, and create predictive algorithms that transform raw security data into actionable insights. Your work will enable security leaders to shift from intuition-based decisions to data-driven strategies backed by rigorous quantitative analysis.
You should be passionate about working with huge datasets and someone who loves to bring datasets together to answer business questions. You bring expertise in machine learning, statistical modeling, and data analysis, and you combine that with curiosity and business judgment to solve ambiguous problems at Amazon scale.
Amazon is continuously innovating new services and features for our customers. Our engineers invent, build, and sometimes break things to make them easier, faster, better, and more cost-effective. However, no matter what we're building-from websites to web services, AR to AI, drones to devices-security is always our top priority. The Amazon Application Security team focuses on working with our builders to provide experiences that our customers can trust. That means constantly learning new things and solving complex problems to protect the safety, security, and privacy of billions of lives on a global scale.
At Amazon, you'll be working with the best minds in technology and security. Learn and be curious here, and accelerate your career growth. You can take pride in knowing that your work is meaningful, having a positive impact on others and making the world a better place.
Key job responsibilities
Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard AI/ML models and working with Large Language Models
With your broad expertise in a variety of data science disciplines, recommend the right data science strategy and drive solutions to complex or ambiguous problems
Develop machine learning models for pattern recognition, classification, and prediction across security domains
Build clustering algorithms that identify root causes and patterns across thousands of security issues
Create statistical models and forecasting algorithms to predict security performance trends and identify improvement opportunities
Design and implement data correlation pipelines that integrate security signals from multiple sources
Work closely with internal stakeholders like business intelligence engineers, data engineers, security teams, and leadership to influence strategies and align solutions with organizational needs
Innovate by adapting new modeling techniques and procedures to solve never-before-solved security problems
Passionate about working with huge datasets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets
Communicate results to diverse audiences of varying technical backgrounds with effective writing, visualizations, and presentations
About the team
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.
AppStar DNA Team (Data & Analytics Engineering)
The AppStar DNA team supports the AppStar organization, which is responsible for securing applications at Amazon. Our team is committed to building world-class data infrastructure that provides the foundation for analytics solutions, enabling visibility into security performance and driving data-informed decision-making across security teams. We work with massive volumes of security data to deliver the infrastructure that powers insights with immediate influence on how Amazon secures its applications and protects customer trust.
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.
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 and 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.
Basic Qualifications
2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment
Preferred Qualifications
Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Experience in defining and creating benchmarks for assessing GenAI model performance
Experience working on multi-team, cross-disciplinary projects
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 - 153,400.00 - 207,500.00 USD annually
