Our mission: To be Earth's most customer-centric company.
Are you looking to solve exciting Fraud challenges in the cloud? Do you want to work on a Cloud business that is growing multiple fold annually? If so, we want to talk to you! We are seeking a talented Research Scientist to help us evolve our processes and to improve customer experience across the globe.
The mission of the Fraud Prevention Team is to keep the AWS platform a safe and trusted place for our customers and partners. We achieve this goal by identifying and preventing fraud and abuse for all AWS services, worldwide. Every day fraudsters attempt to steal our services. We use extensive data and machine learning models to build software solutions to detect and prevent such activities.
As a Research Scientist, you will work directly with other scientists and Software Development Engineers to monitor the flavor/trend of fraud worldwide and create appropriate actions to respond in a collaborative environment. There are no walls, and success is determined by your ability to dive deep, and understand the subtle demands new and complex services will place upon systems and teams.
What would I do?
- Lead day-to-day review of emerging fraud threats and work with the broader team to drive responses to combat them
- Manage your own process: identify and execute on high impact projects, triage external requests, and make sure you bring projects to conclusion in time for the results to be useful
- Apply Statistical and Machine Learning methods to specific business problems and data
- Deep dive on the problems using scripting language like Python, SQL and internal dashboards and drive short term and long term solutions
- Analyze data (past customer behavior, sales inputs, and other sources) to figure out trends, and output reports with clear recommendations.
- Collaborate closely with the development team to recommend innovations based on data analysis
- Handle escalations from AWS Management for Fraud and related activities
- Be the primary point of contact during fraud outbreaks including analyses to identify responses and applying responses.
- Drive the design and development of tools to aid in operations and automation, such as creation of right dashboards to improve monitoring fraud
- Collaborate in a fast paced environment with multiple teams and customers in a dynamic entrepreneurial organization
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.
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.
- Master’s degree in Mathematics, Statistics, Computer Science or in another related field
- 3+ years of hands-on relevant, technical industry experience
- Deep understanding of Statistical Analysis, modeling and Machine Learning techniques
- Experience in designing and deploying ML modeling and prediction pipelines.
- Proficiency in programming/scripting language such as Python or equivalent.
- Ability to write SQL scripts for analysis on heterogeneous data sources.
- Familiarity with AWS RedShift, Spark or other distributed computing technologies.
- Excellent written and verbal communication skills
- Excellent problem solving skills with a strong attention to detail
- Demonstrated skill and passion for operational excellence
- Previous work as a Data Scientist in the context of fraud analytics or risk scoring.
- Experience and proficiency with AWS technologies (EC2, CloudTrail, S3, SageMaker, Lambda, DynamoDB, RDS, etc.), and Big Data technologies.
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Workers in New York City who perform in-person work or interact with the public in the course of business must show proof they have been fully vaccinated against COVID or request and receive approval for a reasonable accommodation, including medical or religious accommodation.