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Goldman SachsPosted 2 weeks ago

Engineering - New York - Associate, Risk Governance - 10427763

$136,000–$154,400 year

On-siteNew York City, New York, United States or New York, United States

Full TimeEntry LevelMasters DegreeEnterpriseInvestment Banking

Job Summary

Identify, analyze, and monitor risks pertaining to business processes and controls, including emerging risks within the operational risk profile. Determine, negotiate, and agree on firm and business quality procedures, standards, and specifications while assessing inherent and residual risks to ensure the Risk and Control Self-Assessment accurately reflects the current environment. Establish effective supervisory structures and governance forums, such as divisional operational risk and resilience councils. Attend regular risk meetings to review exceptions, ask probing questions to establish potential market and client risks, and share best practices across teams to ensure effective controls mitigate exposure. Define thematic RCSA issues to structure remediation plans for significant open risks and aid in executing Control Assurance requirements.

Required Qualifications

  • Master's degree (U.S. or foreign equivalent) in Economics, Finance, Computer Science, or related field
  • Bachelor's degree (U.S. or foreign equivalent) in Economics, Finance, Computer Science, or related field
  • One (1) year of experience in the job offered or a related role (with a Master's degree)
  • Two (2) years of experience in the job offered or a related role (with a Bachelor's degree)
  • Performing statistically driven analysis using various data analytical techniques to identify trends and propose process enhancements
  • Creating, developing, and enhancing probabilistic and deterministic financial models
  • Visualizing complex data analyses from raw data in risk management reports, using visualization tools such as Tableau
  • Communicating results to a wide variety of audiences
  • Leveraging analytics and automation experience to propose effective and efficient methods to enhance testing and sampling strategies to ensure the most effective risk detection and analyses
  • Developing processes and tools to identify and monitor data accuracy

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