Data Scientist - Cyber Security

Job description

DESCRIPTION

Excited by using massive amounts of data to develop machine learning (ML) models for cyber security? Want to help the largest global enterprises operate safely in the cloud and securely derive business value through the adoption of artificial intelligence? Eager to learn from many different enterprise's use cases of AWS ML and security services? Thrilled to be key part of Amazon, who has been investing in machine learning and cyber security, pioneering and shaping the world's technology? Our Professional Services organization works together with our AWS customers to address their security needs – and we are investing in our use of AI, ML, and advanced analytics in this pursuit.

At AWS, we're hiring technical specialists at the convergence of the three hottest areas in tech: Data Science, Cyber Security, and Cloud Services. Are we only hiring magical unicorns with depth of skills in all three…? Nope. You're a great fit for this role if you have hands-on experience in data science and have some exposure to Security or Cloud. We'll help you grow into a unicorn while you work directly with Amazon's biggest customers – leveraging data and analytics to help them find innovative ways to work securely in the cloud.

Responsibilities include:
· Expertise – Customers using AWS are collecting more data than ever before about their network, infrastructure, services, applications, and users. There is a broad canvas of security-related data waiting to be tapped to help our customers know their information resources and keep them safe. You're an expert with data – envisioning scenarios, cleaning data, gaining initial insight, building models, iterating, and bringing action from insight.
· Solutions – You like working with customers to solve problems and identify opportunities in their security approach and implementation. You'll define and deliver on-site technical engagements with partners and customers. This includes not only delivering custom solution engagements, but also participating in pre-sales on-site visits, understanding customer security and compliance requirements, evaluating their data and analytics readiness, and proposing and delivering packaged offerings.
· Delivery - Lead the hands-on execution of customer engagements and internal builder projects. Customer engagements include migration of existing functionality, evolution of existing capabilities and process, and development of new applications using AWS cloud services.
· Practice Development – Helping customers is our number one goal – but it's not our only goal. With each engagement, you're looking for ways to collect, capture, package and share your knowledge with new customers, partners, and AWS employees. You are a force-multiplier – developing tools, services, and new artifacts to help others build on the work you deliver.
Amazon aims to be the most customer centric company on earth. Amazon Web Services (AWS) provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers critical applications for hundreds of thousands of businesses in 190 countries around the world.

Desired profile

BASIC QUALIFICATIONS

· EITHER: Bachelor's Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics) and 5+ years' experience in data science and predictive modeling
· OR: Phd/MTech/MS in Computer Science, Artificial Intelligence/Machine Learning, Mathematics or Statistics and 3+ years' experience in data science and predictive modeling
· Experience using Python and/or R
· Previous experience in a ML or data scientist role and a track record of building ML or DL models
· Ability to travel to customer sites as needed