Job Description Summary:
Global Data Sciences (GDS) is the largest group in PayPal’s Enterprise Services organization. The team comprises data researchers, analysts, modelers, and software engineers. GDS is in charge of implementing unique, best-of-breed fraud-detection algorithms using cutting-edge technologies, and delivering systems which are highly available, scalable, distributed, and process data at web scale to aid in detecting and preventing all forms of fraud and risk affecting the PayPal $240B payments network.
What does Success Look Like?
Come join our team and take the lead on some of our most exciting data engineering and analytics projects, including:
- Design and build massive Big Data analytical solutions utilizing graph, machine learning and text mining algorithms.
- Design and build Data infrastructures and tools leveraging Big Data industry standards and cutting edge frameworks
- Work side by side with analysts to extract meaningful and actionable insights from PayPal data.
- Lead analytical projects from inception through research, development and all the way to production on
- PayPal’s data processing infrastructure
We are Looking for people who are:
- passionate for about technology and for developing robust, scalable, state of the art software systems
- highly motivated, goal driven and have posses a can-do approach
- Innovative, entrepreneurial, team player, great at Ability to multi-tasking, curious and open minded
- B.Sc. in computer sciences/ mathematics or equivalent; or IDF technological unit technology experience
- Proven development experience in Java or/ Scala
- 4+ years’ experience building production software systems
- Linux / other *nix – hands-on experience
- Hands on Some experience with different databases solutions (SQL/NOSQL)
- Excellent English (written and verbal)
- Hands on experience with Big Data and Streaming technologies: Hadoop / Spark / ElasticSearch
- Design and architecture experience, as well as knowledge and experience with object oriented design patterns
- Experience working on large-scale application deployments and performance tuning.
- Experience in text mining/machine learning / graph algorithms