Data Scientist II - AWS Identity & Access, Threat Detection

Amazon Dev Centre Canada ULC Toronto, ON

About the Job

Job summary
AWS Identity is looking for a Data Scientist who is passionate about using data to drive decisions that help improve safety across AWS services and build trust with customers and stakeholders. You'll have the opportunity to raise the bar by helping to develop new systems that automatically defend against evolving threats.

Amazon Web Services (AWS) is a dynamic and rapidly growing business within Amazon, with millions of active customers in 190 countries around the world. We maintain a rapid pace of innovation by treating each team like its own startup inside AWS, directly accountable for their customers’ satisfaction, service innovations, ambitious growth, and meeting revenue goals.

AWS Identity platform provides the bedrock for secure and continuous access to all AWS services. By quickly connecting millions of users, across the world we empower organizations and enterprises to accelerate their cloud and digital transformation.

Data Scientists within AWS Identity need to be creative, responsible, and curious while working with others to move quickly in producing customer solutions. You’re excited about rolling up your sleeves, implementing ideas, and learning from those around you. You relish the opportunity to dig into challenging operational issues, fix them permanently while taking the learning back as you design the next iteration.

This specific position is for the Threat team within the Workforce Identity group that handles AWS account sign up, sign in and Single Sign On (SSO). The position will involve detecting and mitigating threats to AWS.

About Us

Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.



Key job responsibilities
· Implement statistical or machine learning methods to solve specific business problems.
· Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
· Collaborate with researchers, software developers, and business leaders to define product requirements, provide analytical support, and communicate feedback
· Execute end to end insights projects including data collecting, data cleaning, exploratory analysis, model selection, model evaluation, and interpreting results.
· Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes
· Communicate verbally and in writing to business customers and leadership team with various levels of technical knowledge, and share insights and recommendations

BASIC QUALIFICATIONS

· 3 years in Data Science or Statistics and 2+ years work experience
· Experience using at least one statistical software package such as Python, R, Stata, or Matlab.
· Experience with object-oriented programming languages
· Experience using SQL for acquiring and transforming data

PREFERRED QUALIFICATIONS

· 5+ years data science work experience
· Expertise using SQL for acquiring and transforming data
· Outstanding quantitative modeling and statistical analysis skills
· Experience building complex data visualizations
· Experience with causal inference, applied time series modeling or machine learning forecasting applications
· Strong fundamentals in problem solving, algorithm design and complexity analysis
· Excellent communication (verbal and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams


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, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.