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Sr Data Scientist, Vulnerability Management & Remediation

Amazon

Sr Data Scientist, Vulnerability Management & Remediation

Amazon

Austin, TX, USA

·

On-site

·

Full-time

·

1mo ago

Compensation

$159,200 - $215,300

Benefits & Perks

Healthcare

401(k)

Equity

Flexible Hours

Mental Health

Parental Leave

Healthcare

401k

Equity

Flexible Hours

Mental Health

Parental Leave

Required Skills

SQL

Python

Statistical analysis

Machine learning

Data mining

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 pipelines
  • Experience as a leader and mentor on a data science team

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, TX, Austin - 159,200.00 - 215,300.00 USD annually

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L4

0 reports

$181,968

total / year

Base

-

Stock

-

Bonus

-

$154,672

$209,264

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge