Quantitative Risk Analyst

3 weeks ago

Bengaluru, Karnataka, India Goldman Sachs Full time
Risk Economics Strats Team

The Risk Economics Strats team is a critical component of Goldman Sachs' risk management framework, responsible for developing macroeconomic and financial scenarios for firm-wide scenario-based risk management. Our team's primary objectives include:

  • Developing and implementing statistical models for credit loss forecasting, business-as-usual risk management, and regulatory stress testing requirements.
  • Analyzing large datasets of risk metrics to extract valuable insights about the firm's exposures.

To achieve these objectives, our team interfaces with various divisional, finance, and risk management groups across the firm. The cross-disciplinary nature of our projects creates a challenging and multifaceted work environment.

Responsibilities

As a member of the Risk Economics Strats team, you will be responsible for:

  • Researching and developing coding infrastructure and environments to facilitate analysis related to scenario development, portfolio idiosyncratic risk, and credit loss impacts.
  • Designing and implementing models to capture different risk features critical for the estimation of credit loss impacts.
  • Applying statistical and machine learning techniques as required for risk management purposes.
  • Collaborating with other teams to understand different use-cases and develop and refine models.
  • Documenting loss forecasting, stressed capital models, and methodologies for both internal and regulatory requirements.
  • Providing overall support to the team to meet requirements for regulatory stress-testing and business-as-usual risk management calculations.
Qualifications

To be successful in this role, you will need:

  • Strong quantitative and analytical skills with an advanced degree in a quantitative discipline and hands-on experience in handling data, model building, and programming.
  • The ability to quickly learn and utilize quantitative modeling techniques.
  • Excellent written and verbal communication skills.
  • Strong organizational skills, strong communication, and the ability to manage multiple assignments concurrently.
  • Experience with building models for credit ratings, PD/LGD models, and loss forecasting is an additional benefit.
Prior Work Experience

We are seeking candidates with at least 3-5 years of experience in financial modeling, loss forecasting, and business analytics-related roles. Ideal candidates will have experience with statistical techniques, including segmentation, decision trees, and other advanced risk predictive modeling methods. Familiarity with statistical packages (Python, R) and data mining and data manipulation tools on big data platforms (Hadoop, Spark) is preferred. Strong writing, presentation, and communication skills, as well as technical writing and documentation experience, are also desired. Ability to manage multiple assignments concurrently across various stakeholders and operate independently with high degree of ownership and accountability is essential.

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