Finance Data Science Lead

PayPal

(San Jose, California)
Full Time
Job Posting Details
About PayPal
At PayPal, we’re laser focused on creating better ways for consumers and merchants to pay and get paid. Putting customers’ needs first, coupled with a “challenger” mindset, we’re redefining the payments category through product, marketing, and service delivery innovation. PayPal is not for everyone.
Summary
PayPal’s Finance transformation team owns the data platform and forecasting model infrastructure that powers Company-wide short and long term analytics, forecasting and reporting processes for bank and card costs and fraud losses. The transformation team partners with Risk Management, Payment Platform, Finance and Data Technology teams to build state of the art back-end and front-end data and analytics systems that deliver capabilities for undertaking business performance analysis, automated trend deviation alerts, assessment of scenario based financial outcomes of business investments and organization’s financial performance.
Responsibilities
Design best structure and select the most appropriate modeling techniques which include a variety of machine learning algorithms. Analyze data covering a wide range of information from user profile to transaction history. Identify new and emerging patterns through data mining. Build and validate financial forecasting models, provide analysis support, and develop new statistical forecasting criteria and/or techniques Lead and manage the design and optimization of predictive algorithms and / or processes using advanced statistical / mathematical forecasting approaches. Iteratively test, refine and improve the models. On a regular basis, ensure models and methodologies are statistically valid and provide fact based interpretation of performance. Research, analyze and triangulate information on various loss trends to determine significance, assess implications and provide analysis with recommended actions Work with large volumes of data; extract and manipulate large datasets using tools such as SQL, SAS, and Hadoop Closely work with Finance, Risk BU, IT, Engineering and other data/system providers to enhance systems, trouble-shoot data issues, etc.
Ideal Candidate
* Master’s in Mathematics, Statistics, Financial Engineering or equivalent is desired. MBA is preferred * 8-10 years of post-college working experience within a Quantitative Research, Statistical Modeling or Quant FP&A organization * Creative problem solver, analytic thinker, and quick learner. Strong conceptual and creative problem-solving skills; ability to work with considerable ambiguity; ability to learn new and complex concepts quickly. Relentlessly resourceful and scrappy * Required technical skills: MS Excel (with VBA), Teradata SQL and SAS. Working knowledge of Map-Reduce, Hive, R, Pig * Hands-on experience with SAP Bank Analyzer and Tableau is preferred * A great communicator, strong project management skills, and superb attention to details

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