PayPal | Hiring | Data Scientist | BigDataKB.com | 2022-09-16

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Job Location: Chennai

Build, run, and document CECL-compliant loss prediction models for global credit products leveraging internal performance data and various macroeconomic inputs

Communicate complicated analytic results in brief, concise, and brilliant formats best suited to senior audiences

Conduct regular stress testing to ensure the portfolio maintains minimum profitability measures

Participate in monthly/quarterly reserve setting process with Finance and Accounting

Monitor global portfolio performance to ensure its within PayPal s Credit Risk Appetite

Partner with Operations to conceive, design monitor strategies to improve credit losses

Analyze large volumes of internal and external data using common data science tools (SQL, R, Python, etc.) to deliver unique insights into relationships across a wide array of products, platforms, customers, merchants, and experiences.

Functional Skills Behaviors

Basic understanding and Knowledge of machine learning/econometrics

Articulate, executive level presentation and communication skills

Be data-driven and outcome-focused

Must have good business judgment with demonstrated ability to think creatively and strategically

Takes personal ownership; Self-starter; Ability to drive projects with minimal guidance and focus on high-impact work

Learns continuously; seeks out knowledge, ideas and feedback.

Looks for opportunities to build skills, knowledge and expertise.

Comfortable with ambiguity and frequent context-switching in a fast-paced environment

Qualifications

Minimum Bachelor s degree in Mathematics, Statistics, Operations Research, Finance, Economics or related quantitative discipline; preferably an advanced degree.

5+ years of proven Risk and Collections experience in Financial Services, Payment Transactions or other financial-related industry

Analytical and project management experience

Excel and spreadsheet analysis; Handling and building complex formulas in Excel spreadsheet;

Risk Management; Collections strategy; Statistical analysis; Loss modeling; Building complex forecasting model using advanced Excel functions

SQL and Python skills to be able to run data queries and research risk strategy and collections impacts; experience using common data science tools like R and Python to rapidly solve business problems preferred.

PowerPoint user, for management communications and broad organizational readouts

Experience with CECL is a plus (Current Expected Credit Loss)

Apply Here

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