As a Senior Data Scientist on our team, you will leverage advanced analytics and machine learning to protect our cloud infrastructure from security threats. You'll develop and deploy sophisticated anomaly detection models, predictive algorithms, and real-time analysis systems that identify and automate the mitigation of cyber threats across Amazon's infrastructure. Your expertise in statistical analysis, machine learning, and big data processing will be crucial in building scalable security solutions.

You'll collaborate with software engineers, security engineers, and fellow data scientists 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 SageMaker, EMR, and other ML/AI services to protect every AWS customer from security threats. Experience with Python and a strong background in statistical analysis and machine learning 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.

We understand that life is dynamic and we have a flexible work environment that enables individuals to adjust their work schedule to accommodate personal needs. Our team is distributed, though most of the team is located in Maryland and Virginia. We generally keep core business hours of 10:00 AM EST - 3:00 PM EST, while allowing flexibility as needed. At AWS Security, it’s not about clocking hours, it’s about delivering results.

On-Call Responsibility
This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.




Key job responsibilities
- Running experiments to assess potential risk of security responses.
- Expanding our existing LLM prompts to detect new customer signals.
- Analyzing post mortems to understand what data signals could have prevented the occurence

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

PREFERRED QUALIFICATIONS

- Experience managing data pipelines
- Experience as a leader and mentor on a data science team

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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.