Data Scientist, Aws Security

Amazon Amazon · Big Tech · Arlington, VA · Data Science

Data Scientist role focused on leveraging advanced analytics and machine learning to protect AWS cloud infrastructure from security threats. The role involves developing and deploying anomaly detection models, predictive algorithms, and real-time analysis systems, as well as building and expanding LLM agent pipelines. Key responsibilities include analyzing large-scale security data, creating automated systems for threat identification, building data pipelines, and translating analytical findings into actionable insights. Experience with Python, statistical analysis, and machine learning is essential, with a focus on using AWS technologies like SageMaker and EMR.

What you'd actually do

  1. Analyze large-scale security data using statistical methods and data mining techniques
  2. Create automated systems for real-time pattern recognition and risk assessment
  3. Build data pipelines and ETL processes to handle massive security datasets
  4. Translate complex analytical findings into actionable security insights
  5. Expanding our existing LLM agent pipelines

Skills

Required

  • 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
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
  • Python
  • statistical analysis
  • machine learning

Nice to have

  • 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 applying quantitative analysis to solve business problems and making data-driven business decisions

What the JD emphasized

  • protect our cloud infrastructure from security threats
  • identify and automate the mitigation of cyber threats
  • building scalable security solutions
  • protect every AWS customer from security threats
  • LLM agent pipelines

Other signals

  • anomaly detection models
  • predictive algorithms
  • real-time analysis systems
  • LLM agent pipelines