The Risk division is responsible for credit, market and operational risk, model risk, independent liquidity risk, and insurance throughout the firm.

　　Responsibilities:

　　Support credit risk management senior leadership in partnering with business units and broader Credit department to assess data availability, data sufficiency, and reporting needs Design and write data queries to extract credit data from credit systems and conduct analysis of portfolio performance, deep dive analysis of trends, summarize findings and recommend changes Ability to identify existing and emerging drivers of risk in a portfolio to drive guardrail design and proactive management of the portfolio. Create guardrails/ thresholds across various dimensions Provide support for portfolio credit risk oversight and governance by tracking the actual performance of risk appetite and credit risk management metrics against approved guardrails Create Management reporting using Tableau or other cutting-edge visual interface-based tools to monitor portfolio performance at portfolio segment level (e.g., product, vintage, risk segment, score band, or marketing channel) Develop analytical reports and presentations for senior management, executive committees and regulatory exams. Be up to date on applicable regulations and compliance requirements in consumer lending and provide support to Senior Leadership during interactions and updates to internal and external regulators Adhere strictly to compliance and operational risk controls in accordance with company and regulatory standards, policies and practices Address internal audit requirements and findings in a timely and appropriate manner

　　Qualifications:

　　3+ years related industry experience Strong quantitative and analytical skills Master's degree (U.S. or equivalent) in a quantitative discipline such as Mathematics, Statistics, Engineering, Data Science/Analytics or a related field like Information Systems, Business Analytics. Experience building, improving, or analyzing risk policies in a consumer or small business lending or similar data driven industries such as insurance Experience in unsecured consumer lending (e.g., installment loans, credit cards) preferred and expertise with credit bureau data as well as familiarity with alternate credit related data sources Experience in retail credit risk analytics including 5+ years of retail strategy with credit policy/underwriting criteria development, performing portfolio deep dive analytics including performance measurement and insight generation to influence credit policy Knowledge of U.S. credit bureau data, Risk Scorecards to drive analysis and outcome Experience using statistical packages like SQL, SAS, R, Python etc., tools to mine, manipulate & aggregate complex consumer and transaction level data on big data platforms such as Hadoop, Spark etc. Statistical techniques such as decision trees, regression modeling, machine learning, testing techniques and time series data analysis techniques. Visualizing information/ trends from raw and complex data using visualization tools such as Tableau, and communicating results to a wide variety of audiences Advanced Microsoft Office skills, specifically Excel (including creation of pivot tables, logic functions), PowerPoint and Word Strong writing, presentation and communication skills; technical writing and documentation experience desired Strong project management / organizational skills and the ability to manage multiple assignments concurrently across various stakeholders Ability to do end-to-end project delivery ABOUT GOLDMAN SACHS

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