June 24, 2022
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London, United Kingdom
June 24, 2022
Apply NowJob description
- Master’s degree in Mathematics, Statistics, Computer Science or in another related field, or equivalent years of industry experience
- Several years of hands-on relevant experience using programming/scripting languages such as Python or equivalent
- Proven understanding of Statistical Analysis, Modeling and Machine Learning techniques
- Experience in designing and deploying ML modeling and prediction pipelines
- Ability to leverage SQL or Spark for Ad-hoc analyses and building out ETL pipelines on heterogeneous data sources
- Experience performing statistical analysis and using tools such as R, pandas, or equivalent
Job summary
Do you want to detect and mitigate attacks against AWS? The Identity Threat teams create automated tooling to detect attacks against the AWS Front Gates (Sign-in and Sign-up) and automate the mitigations. We are looking for someone who wants to be involved with a team that has low operational overhead while providing large scaling challenges, big data obstacles, and fun problem solving (how to detect someone that does not want to be found!).
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.
The AWS Identity Threat team based out of the UK gathers and processes the major signals that influences what all other teams might do. Data Scientists on this team have great opportunities to see vast quantities of data to build new models that can greatly enhance our detection capabilities or perform research that can identify new opportunities for the organization that may overhaul everyones roadmap. The role does not require specific security or threat experience.
Key job responsibilities
As a Data Scientist for the Identity org, your responsibilities will include:
A day in the life
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.
Do you want to detect and mitigate attacks against AWS? The Identity Threat teams create automated tooling to detect attacks against the AWS Front Gates (Sign-in and Sign-up) and automate the mitigations. We are looking for someone who wants to be involved with a team that has low operational overhead while providing large scaling challenges, big data obstacles, and fun problem solving (how to detect someone that does not want to be found!).
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.
The AWS Identity Threat team based out of the UK gathers and processes the major signals that influences what all other teams might do. Data Scientists on this team have great opportunities to see vast quantities of data to build new models that can greatly enhance our detection capabilities or perform research that can identify new opportunities for the organization that may overhaul everyones roadmap. The role does not require specific security or threat experience.
Key job responsibilities
As a Data Scientist for the Identity org, your responsibilities will include:
- Apply state-of-the-art Machine Learning methods to large amounts of data from different sources to build and productionalize detection and mitigation solutions
- Deep dive on the problems using SQL and scripting languages like Python/R to drive short term and long term solutions leveraging Statistical Analysis
- Analyze data, for example past customer behaviour, to figure out trends, create compromise prevention and mitigation solutions and output reports with clear recommendations
- Collaborate closely with the development team to recommend and build innovations based on Data Science
- Manage your own process: identify and execute on high impact projects, triage external requests, and bring projects to conclusion in time for the results to be useful
- Providing on-call product support approximately once every 2-3 months
A day in the life
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.
- Experience and proficiency with AWS technologies (EC2, CloudTrail, S3, SageMaker, Lambda, DynamoDB, RDS, etc.), and Big Data technologies
- Familiarity with AWS Redshift, Spark or other distributed computing technologies
- Previous work as a Data Scientist in the context of fraud analytics or risk scoring
- Ability to work in a fast-paced, ambiguous environment while prioritizing and managing multiple responsibilities
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
