The Risk Feature Engineering platform works on software and services to provide easy to onboard, scalable feature engineering solutions for batch, streaming and real time features for ML rules and models for RIsk & Safety teams. You will be part of a team of strong software engineers executing in a fast paced environment. For more information of example of work tackled by Risk as a whole, see these blog posts:
Protect all Uber customers across all product lines (Rides, Eats, Freight, Uber for Business, Uber Everything) globally from fraudsters
Drive down global payment fraud
Build rich user experiences that not only block bad users but also make the in-app experience fluid and rich for our good users.
What you will do:
Detect fraudulent behavior through Machine Learning by leveraging account, location and device signals
Designing and developing backend systems infrastructure leveraging Cassandra, Hadoop/Hive, Flink and other Uber internal infrastructure platforms.
Work closely with a fun and highly collaborative cross-functional team of Engineers, Product Managers, Data Scientists, Data Analysts and Risk Analysts
Basic Qualifications:
At least two (2) years of software engineering experience
Bachelor of Science (BS) in Computer Science, Physics, or Mathematics, or related field
Experience coding with C, Java, Python, or Go
Experience developing and shipping code for production systems
Experience in systems software engineering. Sound understanding of computer architecture and CS fundamentals.
Proficient in one of the following programming languages: Java or Golang or other equivalent
Preferred Qualifications:
Detailed problem-solving approach and knowledge of algorithms, data structures, and complexity analysis.
Understanding of distributed system and architecture