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)
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