Data Scientist - Fraud Prevention Team

Company:
Location: Berlin

*** Mention DataYoshi when applying ***

  • Master’s degree in Mathematics, Statistics, Computer Science or in another related field.
  • 2+ 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.
  • Ability to leverage SQL or Spark for Ad-hoc analyses and building out ETL pipelines on heterogeneous data sources.
  • Experience using programming/scripting languages such as Python or equivalent.
  • Experience performing statistical analysis and using tools such as R, pandas, or equivalent.
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.

About the Team. 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 fraudulent activity? If so, AWS Fraud Prevention has an exciting opportunity for you.

The AWS Fraud Prevention Sign-Up and New Services vertical is responsible protecting the AWS Registration pipeline, compute based and other new services from fraudulent activity.
You’ll be part of a team of Data Scientists, Investigations Analysts, and Technical & non-Technical Program Managers. The team’s mission is to prevent, detect and mitigate bad actors from committing fraud on our platform.

About the Role. As a Data Scientist, you will work directly with Business Analysts and Software Development Engineers to monitor the flavor/ trend of fraudulent activity 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. As a Data Scientist your responsibilities will include:
  • Protecting AWS customers and the AWS business from fraudulent actors.
  • 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 state-of-the-art Machine Learning methods to large amounts of data from different sources to build and productionalize fraud prevention, detection and mitigation solutions.
  • Keep up with and contribute to the progress of the Amazon and broader ML research communities in the context of fraud prevention.
  • 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 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.
  • Handle escalations from AWS Management for fraud, compromise and related activities.
  • Be the primary point of contact during outbreaks – including analyses to identify and apply responses.
  • Collaborate in a fast paced environment with multiple teams and customers in a dynamic entrepreneurial organization.
Learn and Be Curious. We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members.

  • 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.
  • Excellent written and verbal communication skills.
  • Excellent problem solving skills with a strong attention to detail.
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.

Learn more about Amazon on our Day 1 Blog: https://blog.aboutamazon.com

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 to know more about how we collect, use and transfer the personal data of our candidates.

*** Mention DataYoshi when applying ***

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