Sr Data Scientist, Vulnerability Management & Remediation

This job is with Amazon, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

DESCRIPTION:

As a Senior Data Scientist on our team, you will leverage advanced analytics and machine learning to provide insights and expose risk in our Vulnerability Management systems. You'll develop and deploy sophisticated anomaly detection models, predictive algorithms, and real-time analysis systems that identify flaws in our findings pipeline. Your expertise in statistical analysis, machine learning, large language models, and big data processing will be crucial in building scalable security solutions.

You'll collaborate with software engineers, security engineers, business intelligence engineers and managers to:

- Analyze large-scale security data using statistical methods and data mining techniques
- Create automated systems for real-time pattern recognition and risk assessment
- Build data pipelines and ETL processes to handle massive security datasets
- Translate complex analytical findings into actionable security insights

We use the full power of AWS technologies, including Amazon Sage Maker, EMR, and other ML/AI services to monitor, enhance, automate, and report on our security risks.

Experience with Python and a strong background in statistical analysis, machine learning, and data mining are essential.

We're looking for a new teammate who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers. We want someone who will help us amplify the positive & inclusive team culture we've been building.

Key job responsibilities
- Advising and co-architecting data warehouse solutions to optimize operations and reporting
- Building pipelines to automate the business
- Running experiments to identify and rectify data and system anomalies
- Expanding our existing LLM prompts to automate and baseline security review, and
- Analyzing out contextualization outputs to ensure continuous optimal severity assignments

About the team
Diverse Experiences
Amazon Security values diverse experiences. Even if you do not meet all of the 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.

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 & 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.

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.

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
- Bachelor's degree

PREFERRED QUALIFICATIONS:

- Experience managing data…