Sr. Data Scientist - Security, Global Services Security

Key Skills

AWS, CNNs, MATLAB Programming, Python Programming, PyTorch, RNNs, SAS, SQL, TensorFlow

Job Description

The Global Services Security (GSS) team at AWS is seeking a talented data scientist to help lead adoption of AI/ML in our products and services. GSS is responsible for delivering product-led, people-powered services that help our customers operate their business securely on AWS, and we are accelerating our adoption of AI/ML. This is an exciting opportunity to contribute at the intersection of AI/ML, cloud, and cyber security. Your primary responsibility will be to envision, experiment, prototype, and mature to scale AI/ML solutions in our products to meet the needs of our customers. You will have the opportunity to work with multiple lines of business, and learn from (and contribute to) a variety of security use cases. This is a hands-on role where success is measured by producing solutions that have measurable impact.

The GSS team leverages the expertise and ingenuity of our builders to establish scalable security solutions for both internal and external customers that drive business outcomes. Our goal of securing the world’s workloads and building a brighter future for humanity requires us to focus on reliable delivery of bar raising security outcomes and investment in security mechanisms and automation on behalf of our customers.

Key job responsibilities

• Advocate for the proper use of AI/ML for security across GSS and Global Services generally. Help guide, teach, and influence others about AI/ML.
• Partner with multiple business lines of GSS to understand security use cases and identify appropriate AI/ML opportunities.
• Design and execute experiments and proofs-of-concept in AI/ML models to help our business teams determine the feasibility and fit of AI/ML solutions.
• Collaborate with other science teams at Amazon to consistently iterate and improve our AI/ML solutions.
• Build AI/ML models that meet or exceed business requirements for performance and responsibility.
• Work with our software engineering teams to help them deliver scalable, maintainable AI/ML-based solutions.
• Contribute to GSS culture and activities for building a brighter future for humanity.

A day in the life

Your day (or week) is a mix of meeting with product and service owners in GSS, sharing information and guidance, and doing hands-on modeling. In the morning, you meet with one of the product teams to understand their user stories and identify the right opportunities for AI/ML. After your meeting this morning about the experimental results, you have two more variations to try before a final decision can be made with the product team. Alternatively, you might pick up where you left off tuning your model for a different product that’s further along. Your accuracy and recall meet the thresholds the product team thinks customers will expect, but you think you can get a few percentage point improvement after talking with some data science colleagues in our Professional Services team last week. Before you close things down for the day, you do a quick check of your on-line messages to see if anything urgent arose while you were head-down on the ML work - but there’s nothing there that can’t wait until tomorrow.

About the team

The GSS team is seeking a talented data scientist to help lead adoption of AI/ML in our products and services. GSS is responsible for delivering product-led, people-powered services that help our customers operate their business securely on AWS, and we are accelerating our adoption of AI/ML.

https://amazon.jobs/en/internal/landing_pages/aws-global-services?offset=10&result_limit=10&sort=relevant&distanceType=Mi&radius=24km&latitude=&longitude=&loc_group_id=&loc_query=&base_query=&city=&country=®ion=&county=&query_options=

We are open to hiring candidates to work out of one of the following locations:

Arlington, VA, USA | Austin, TX, USA | Dallas, TX, USA | Herndon, VA, USA | Houston, TX, USA | Irving, CA, USA | Nashville, TN, USA | New York, NY, USA | Seattle, WA, USA

BASIC QUALIFICATIONS

• Bachelor's degree
• 4+ years of data scientist experience
• 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 5+ years previous experience in a ML or data scientist role, with experience of training and deploying ML models
• Previous experience working with deep learning frameworks and architectures such as MXNet, TensorFlow, PyTorch, CNN/RNN/LSTM, Autoencoders, Transformers

PREFERRED QUALIFICATIONS

• 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
• Experience managing data pipelines
• Experience as a leader and mentor on a data science team
• Phd/MTech/MS in Computer Science, Artificial Intelligence/Machine Learning, Mathematics or Statistics
• Experience with AWS AI services (e.g., Amazon Comprehend), ML platforms (Amazon SageMaker), and frameworks (e.g., MXNet, TensorFlow, PyTorch, SparkML, scikit-learn)

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.