Data Scientist , Global Services Security Engineering

$125,500 - $212,800/Yr

Amazon - New York, NY

Full-time - Mid Level

New York, NY

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

Amazon Web Services (AWS) is seeking talented scientists to join the Security Innovation team within AWS Global Services Security (GSS). This role focuses on leveraging AI/ML technologies to enhance security solutions for AWS customers. The position involves envisioning, prototyping, and scaling AI/ML solutions to address various security use cases, collaborating with multiple business lines, and producing impactful results in a hands-on environment.

Responsibilities

• Identify viable ML opportunities by collaborating with security and business teams, developing plans from experiments to proof-of-concept to software product.
• Explore data to find impactful combinations of transformations and analysis approaches, validating hypotheses and identifying new analytics opportunities.
• Rapidly design, prototype, and test hypotheses in a high-ambiguity environment, reporting results scientifically.
• Partner with AI/ML scientists and architects to pursue new data science approaches for real-world issues.
• Collaborate with software engineering teams to integrate successful experiments into large-scale production services.
• Contribute to best practice recommendations, tutorials, blog posts, sample code, and presentations for various stakeholders.

Requirements

• Bachelor's degree and 5 years of experience or Master's degree and 2 years of experience.
• 3+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab).
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods, and/or machine learning.
• 3+ years of experience using Python and hands-on experience building models for business applications with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet.

Nice-to-haves

• Hands-on experience with deep learning techniques (e.g., CNN, RNN, LSTM, Transformer) and training Large Language Models (LLMs).
• Experience with a broad set of ML approaches including traditional classification, clustering, time series analysis, anomaly detection, and Bayesian non-parametric methods.
• 6+ years of relevant industry experience.
• 1+ years of experience in information security, threat detection, or related domains.
• Experience in production-level software development.

Benefits

• Flexible work hours and arrangements.
• Mentorship and career advancement resources.
• Diverse and inclusive workplace culture.