Data Scientist

Vor 5 Tagen

Berlin, Deutschland Amazon Development Center DEU Vollzeit

Master’s degree in Mathematics, Statistics, Computer Science or in another related field
- 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

Would you like to join the team that protects the global AWS platform from fraud? Do you enjoy thinking like a fraudster and using your technical skills to help detect & mitigate AWS accounts from being compromised? If so, AWS Fraud Prevention has an exciting opportunity for you.

AWS has the most services and more features within those services, than any other cloud provider-from infrastructure technologies like compute, storage, and databases-to emerging technologies, such as machine learning and artificial intelligence, data lakes and analytics, and Internet of Things. AWS Platform is the glue that holds the AWS ecosystem together. Whether its Identity features such as access management and sign on, cryptography, console, builder & developer tools, and even projects like automating all of our contractual billing systems, AWS Platform is always innovating with the customer in mind. The AWS Platform team sustains over 750 million transactions per second.

The AWS Fraud Prevention Compromise vertical is responsible for detecting & mitigating AWS account compromise. You’ll be part of a team of Data Scientists, Investigations Analysts, and Technical & non-Technical Program Managers. The team’s goal is to identify and neutralize fraudsters from compromising AWS customers’ accounts.

As a Data Scientist, you will work directly with Business Analysts and Software Development Engineers to monitor the flavor/ trend of compromise on AWS worldwide and design appropriate solutions 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.
- 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 (past customer behavior, sales inputs, and other sources) 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 make sure you bring projects to conclusion in time for the results to be useful
- Providing on-call product support approximately once every 3 months

On Call Responsibility. This position involves on-call responsibilities to support emergent customer impacting events. Our on-call fraud escalation support occurs approximately once every 12 weeks.

Inclusion and Diversity. Our team is diverse We drive towards an inclusive culture and work environment. We are intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Team members are active in Amazon’s 10+ affinity groups, sometimes known as employee resource groups, which bring employees together across businesses and locations around the world. These range from groups such as the Black Employee Network, Latinos at Amazon, Indigenous at Amazon, Families at Amazon, Amazon Women and Engineering, LGBTQ+, Warriors at Amazon (Military), Amazon People With Disabilities, and more.
- 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

m/w/d

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