Analytics at Ebay

Primary Job Responsibilities
This role is for a corporate level initiative that will leverage cutting edge technologies in analytics, data mining, advanced statistics, visualization, stream processing and many other multi-disciplinary technologies. This role offers a unique opportunity to innovate and work with data, technology, and people from all eBay companies (Market Places, PayPal, Skype, StubHub, Shopping.com, etc).

• Be the lead analyst to support a major new analytical initiative involving eBay subsidiaries – Marketplaces (eBay.com), PayPal and Skype
• Work with Product Management partners to understand fraud reduction use cases and evaluate benefits
• Reduce losses by analyzing and correlating fraud patterns across the three platforms and suggesting new models, techniques, and technology
• Accelerate favorable risk treatment for new and recent users by analyzing and correlating legitimate use across the three platforms
• Explore the use of traditional and advanced statistical techniques like logistic regression, Bayesian trees, decision trees, machine learning/neural networks, clustering, link analysis, graph theory and network theory to gain new insights on cross-company data, which in turn result in actionable ways to reduce fraud and risk without compromising business growth
• Applying risk/fraud models to predict and control risk associated with new accounts, and to combat credit card fraud, bank account fraud, identity theft fraud, spoof fraud etc.
• Preparing and extracting data from large databases.
• Analyzing data covering a wide range of information from user profile to transaction history. Identifying new fraud patterns through data mining.

Job Requirements

• Strong academic profile including an undergraduate or graduate degree in Statistics, Mathematics, Computer Science, Physics, Operations Research and Econometrics
• Experience in analyzing massive and highly complex data sets, performing ad-hoc analysis and data manipulation
• Familiarity with standard statistical analysis techniques and model development techniques
• Ideal candidate would have one or more of the following
• Applications of statistical techniques to real world problems
• Understanding of risk management techniques (e.g., logistic regression, score carding etc)
• Ability to package and present analysis to a senior audience; in particular, the ability to simply communicate complex ideas to diverse business and technology audiences
• Ability to work with large cross-functional teams
• Strong “business/common sense” for the potential of analyses to produce short-term and long-term business benefits
• Ability to deal with ambiguity in terms of requirements and timelines
• 3years of experience in data management and quantitative analyses
• Expert skills in SQL and SAS (on SQL Server, Oracle, or Teradata)
• Strong skills in Excel, Access, and PowerPoint
• Strong skills in major statistical packages (e.g., SAS, Matlab, SPSS)

Education
Bachelors Degree Required

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