Jobs

Team
This position is part of the Trust and Safety (TnS) business unit. We are a small team responsible for applying advanced technology research to solve TnS business problems. TnS applications proactively prevent fraud, catch fraud, enforce eBay policies, as well as collect & mine data that will help build future Trust and Safety strategies.

As our team is relatively new and growing, we provide a challenging, fast paced work environment with plenty of growth opportunities.

Responsibilities

1. Design and build predictive features, analyzing terabytes of historical data.
2. Apply data mining, machine learning, graphical algorithms, statistical and other advance technologies to predict fraud based on significantly rich and extremely large datasets.
3. Aggregate, synthesize, and analyze large amounts of data across DB & log files using SQL / Python / Perl etc.
4. Deploy the learned systems into production where they need to process 100s of millions of transactions per day.
5. Work with a large cross functional team consisting of scientists and engineers from eBay research and engineering teams, as well as analysts and business leaders from TnS and other business teams.
6. Provide guidance to other team members on various techniques and configurations.

Qualifications

1. MS / BS in EE, CS or related engineering field with 3+ / 5+ years of related experience. Or PhD in computer science and 2 years of related experience
2. A strong technology and data analysis background with some machine learning education or exposure.
3. Strong understanding of machine learning: neural networks, Bayesian techniques, scalable clustering algorithms etc.
4. Hands-on SQL experience.
5. Good communication skills, ability to work with large cross functional teams.
6. Some experience with an ETL tool like Abinitio or Informatica or scripting technologies like Python / Perk.
7. Experience / interest in internet / e Commerce / Web 2.0 companies is a plus.

Contact:
pgee@ebay.com