Help craft the future of how Amazonian’s access customer data. You and your team are charged with securing the endpoints that Amazonians use in over 100+ countries around the world.
As a Senior Data Scientists, you lead science and Machine Learning investments to scale out endpoint security automation and Data Loss Prevention controls for endpoint devices.
You will innovate in driving high degrees of accuracy, precision and recall in an ocean of data. You will partner closely with Data Engineers, Business Intelligence Engineers, and Software Engineers to build scalable solutions that must operate in real-time.
Your work will make a difference in this space for the thousands of representatives who use our tool and the millions of customers they support.
Key job responsibilities
- You will extract insights and clarity from noisy, unstructured data arriving in high-volumes.
- You will scientifically test ways to find, measure and long-term solve potential security problems using endpoint telemetry both historical and in real-time.
- You will lead the charge in establishing new techniques to apply Machine Learning and statistical methods to real-time Data Loss Prevention controls that balance speed (microseconds to milliseconds for inference) with accuracy (we deal with billions a day).
A day in the life
We own and drive the endpoint security posture and solutions across Amazon Stores that operate customer support functions.
We own products, programs and engineering that institute security controls to protect customers and their data as Amazonians use it to solve customer issues.
You will work closely with security products, programs and engineering to generate and prioritize experiments, proofs-of-concepts, initiatives and shepherd / steer engineering deliverables.
You will mature the practice of data science in application of security controls and automation. You will innovate to find statistical and Machine Learnign methods that can be practically deployed for real-time blocking or redaction of customer data.
About the team
About AmSec : Diverse Experiences
Diverse Experiences
Amazon Security values diverse experiences. Even if you do not meet all of the preferred 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.
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 flexible work hours and arrangements are part of our culture.
When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
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 and 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.
BASIC QUALIFICATIONS
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
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
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
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