Internal Audit

**Internal Audit - Model Risk (Analyst/Associate, Bengaluru)**

In Internal Audit, we ensure that Goldman Sachs maintains effective controls by assessing the reliability of financial reports, monitoring the firm’s compliance with laws and regulations, and advising management on developing smart control solutions. Our group has unique insight on the financial industry and its products and operations. We’re looking for detail-oriented team players who have an interest in financial markets and want to gain insight into the firm’s operations and control processes.

At Goldman Sachs, our culture is one of teamwork, innovation and meritocracy. We often say our people are our greatest asset and we take pride in supporting each colleague both professionally and personally. From collaborative work spaces and mindfulness classes to working from home and flexible work options, we offer our people the support they need to reach their goals in and outside the office.

**JOB SUMMARY**

The Model Risk team within Internal Audit (IA) at Goldman Sachs is a group of quantitative experts charged with reviewing complex financial models utilized by the Firm as part of various audits with the objective to assess the robustness of the firm’s model risk management framework. The Model Risk team is responsible for a diverse array of model types including models used for valuation of financial products, models used for risk management, capital calculation, compliance, algorithmic trading and investment management models.

The Goldman Sachs Group, Inc. is a leading global financial services firm providing investment banking, securities and investment management services to a substantial and diversified client base that includes corporations, financial institutions, governments and high-net-worth individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in London, Frankfurt, Tokyo, Hong Kong and other major financial centers around the world.

IA supports the Audit Committee of the Board of Directors and senior firm leadership in fulfilling their oversight roles by independently assessing the firm’s internal control structure, raising awareness of control risk, and monitoring the implementation of management’s control measures.

**JOB RESPONSIBILITIES**
- Develop and maintain an in-depth technical knowledge of modeling - both theory and coding
- Critical review of models including their conceptual soundness, documentation, code implementation accuracy and independent validation
- Conduct meetings with stakeholders including modelers and model validators
- Execute risk-focused audits of modeling and model risk management
- Engage in continuous monitoring of modeling and model risk areas
- Communicating modeling problems and issues to senior management

**BASIC QUALIFICATIONS**
- Team-oriented with a strong sense of ownership and accountability
- Strong leadership, interpersonal and relationship management skills
- Strong verbal and written communication skills and presentation skills (PowerPoint, Visio, etc.)
- Highly motivated with the ability to multi-task and remain organized in a fast-paced environment
- Advanced Degree (preferably PhD or Masters) in a quantitative discipline (Math, Statistics, Physics, Engineering, Computer science)

**PREFERRED QUALIFICATIONS**
- Experience within the financial services industry is a plus.
- Product Specific Skills and Experience
- Knowledge of financial modeling concepts, including (any combination):

- Options pricing, credit default, structured products, econometrics, stress scenario creation
- Any combination of risk management disciplines: credit risk, market risk, operational risk, funding / liquidity risk Knowledge in any of the following areas is preferred:

- Risk measurement theory (Value-at-Risk, stress testing etc.)
- Basel Capital Accord regulatory requirements (advanced model-based frameworks)
- Controls surrounding model risk governance, model development, implementation and change management, model validation (Regulatory Guidance SR 11-7)
- Programming experience in quantitative and object oriented programming environments, e.g. Matlab, C++, C#, Python, Java, R, etc.