Data Scientist II, Stores Security, Risk Engineering

Amazon•Seattle, WA

About The Position

Are you passionate about transforming how Amazon identifies and remediates security risks at scale? Does the prospect of using data science and AI to protect Amazon's most critical business operations excite you? Stores BST Risk Engineering builds data-driven risk intelligence solutions that help security teams across Amazon's stores identify, prioritize, and remediate strategic security risks. Our customers range from security engineers managing thousands of vulnerabilities to business leaders making strategic risk decisions. We use machine learning, generative AI, and large-scale data analysis to solve diverse security risks at a very large scale. Your responsibilities will include developing machine learning models for automated fraud detection and pattern recognition, building clustering algorithms that identify root causes across thousands of security issues, and creating data correlation pipelines that integrate security signals from multiple sources. You'll use advanced AI and Data Science techniques for fraud detection, unsupervised learning for pattern discovery, and generative AI for automated analysis at scale. Your work will directly enable security teams to shift from manual analysis taking weeks to automated insights delivered in minutes. We're looking for data scientists who can prototype and productionize innovative models using supervised, unsupervised, and reinforcement learning techniques. You'll work on problems like correlating external threat intelligence with asset inventories, building statistical profiles to detect evolving fraud patterns, and designing confidence scoring systems for real-time risk categorization. If you want to apply machine learning to never-before-solved security problems at Amazon scale, this is your team. About Amazon Security 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Requirements

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

Nice To Haves

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

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 solution to complex or ambiguous problems
Work closely with internal stakeholders like the business teams, engineering teams and partner teams, influence their strategies to align with your focus area
Innovate by adapting new modeling techniques and procedures
Passionate about working with huge data sets ( training/fine tuning) and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets
Exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive.
Show good judgment when making trade-offs between short-term customer, market, or research needs and long-term operations or technology needs.

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

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