Private Non-Financial Risk Associate - AI & Automation

Goldman Sachs Bank AG; Texas; On-site; USD 110,000 - 165,000; Full time

Job summary

Goldman Sachs seeks a risk professional to support the GBM Private Non-Financial Risk Management team, focusing on strategic, operational and compliance risk. You will analyze key risks, drive improvements, and partner with risk managers across Front Office, Operations and Engineering to strengthen the control environment.

The role emphasizes automation, data quality, and innovation through AI-driven risk monitoring and reporting. 1–3 years of relevant experience and a 4-year degree are expected.

Qualifications

• Experience in non-financial risk disciplines such as operational risk management, enterprise risk, compliance or audit preferred.
• Strong analytical skills and curiosity for how risks arise and how controls can be improved.
• Excellent written and verbal communication across stakeholders at all levels.

Responsibilities

• Monitor and report on key risk metrics (KRIs/KPIs); identify opportunities to automate reporting with AI-driven tools.
• Prepare risk conclusions for GBM senior management and key stakeholders.
• Investigate incidents; assess residual risks and advise on remediation.
• Conduct risk reviews and recommend control enhancements to close gaps.
• Collaborate across Front Office, Operations and Engineering to implement integrated risk solutions.
• Identify and implement automation opportunities and AI/machine learning applications in risk processes.

Skills

Risk analytics

Non-financial risk

Stakeholder comms

Automation mindset

Team collaboration

Education

Bachelor’s in finance/accounting/quantitative

Graduate degree in related subject

Tools

Python

VBA

Data visualization

AI/ML risk tools

Job description

Goldman Sachs seeks a risk professional to support the GBM Private Non-Financial Risk Management team, focusing on strategic, operational and compliance risk. You will analyze key risks, drive improvements, and partner with risk managers across Front Office, Operations and Engineering to strengthen the control environment.

The role emphasizes automation, data quality, and innovation through AI-driven risk monitoring and reporting. 1–3 years of relevant experience and a 4-year degree are expected.