From: Gee, Phil
Date: 05 Dec 2007
Subject: San Jose, CA: Data mining scientist, Applied Research at eBay
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
As our team is relatively new and growing, we provide a challenging, fast paced work environment with plenty of growth opportunities.
- Design and build predictive features, analyzing terabytes of historical data.
- Apply data mining, machine learning, graphical algorithms, statistical and other advance technologies to predict fraud based on significantly rich and extremely large datasets.
- Aggregate, synthesize, and analyze large amounts of data across DB & log files using SQL / Python / Perl etc.
- Deploy the learned systems into production where they need to process 100s of millions of transactions per day.
- 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.
- Provide guidance to other team members on various techniques and configurations.
- 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
- A strong technology and data analysis background with some machine learning education or exposure.
- Strong understanding of machine learning: neural networks, Bayesian techniques, scalable clustering algorithms etc.
- Hands-on SQL experience.
- Good communication skills, ability to work with large cross functional teams.
- Some experience with an ETL tool like Abinitio or Informatica or scripting technologies like Python / Perk.
- Experience / interest in internet / e Commerce / Web 2.0 companies is a plus.