Seasonal Portfolio Risk Management Jobs (NOW HIRING)

The Investment Risk team is a key functional area within Global Atlantic, bridging Investments and Risk Management. The team is responsible for independently measuring, monitoring, challenging, and communicating asset-side risk across the enterprise, with a focus on helping the firm make better decisions around asset allocation, sourcing, capital, liquidity, ALM, and downside risk.

We are seeking an experienced Investment Risk professional with strong quantitative and technical skills. The ideal candidate will have experience in portfolio management, investment risk, asset management, insurance, or a related field, and will be comfortable analyzing portfolios, using data, and AI-enabled tools to build scalable analytics, reporting, and strengthen the team's execution of the Investment Risk program.

This is a hands-on role for someone who can combine risk judgment with a builder mindset: translating portfolio questions into practical models, dashboards, workflows, and decision-support tools.

• Design and enhance portfolio risk monitoring frameworks across public and private credit, structured products, mortgage and real estate exposures, alternatives, derivatives, and other insurance-relevant asset classes.
• Build integrated risk views that consolidate exposures by asset class, legal entity, rating, sector, geography, liquidity tier, capital usage, and cross-asset risk factor.
• Develop quantitative analytics for credit, spread, interest rate, liquidity, capital, concentration, valuation, regulatory, and legal-entity risk.
• Support pro forma risk analysis of future sourcing, including the impact of new investments on capital, liquidity, ALM, expected loss, stress loss, concentration, and risk-adjusted return.
• Conduct scenario analysis and stress testing across credit recession, higher-for-longer rates, CRE refinancing risk, consumer credit deterioration, liquidity stress, FX collateral stress, and regulatory capital changes.
• Automate key risk reporting and controls using Python, SQL, and AI-enabled tools, including recurring metrics for rate risk, spread risk, downgrades, capital consumption, liquidity usage, concentrations, and early-warning indicators.
• Develop practical tools and dashboards to support risk appetite monitoring, limit utilization, watchlists, restructuring review, new-deal assessment, and senior management reporting.
• Apply AI and automation to improve document review, data quality checks, reporting workflows, surveillance, code development, and investment risk analysis, while maintaining appropriate governance, auditability, and human review.
• Prepare clear written analysis and presentation materials for Investment Committee, Portfolio Risk Reviews, senior management, and Board-level discussions.
• Partner with Investments, Portfolio Construction, ALM/Actuarial, Valuation, and KKR asset-class deal teams to connect asset-level analysis to enterprise risk decisions.

• 6+ years of relevant experience in investment risk, portfolio management/analytics, asset management, insurance, fixed income, structured credit, quantitative research, data science, or a related field.
• Bachelor's or Master's degree in Mathematics, Economics, Engineering, Computer Science, or another quantitative discipline.
• Strong knowledge of investments and risk drivers across fixed income and equity-like assets; experience with insurance general account portfolios, structured credit, private credit, real estate debt, CLOs, ABS, RMBS/CMBS, or illiquid assets is preferred.
• Advanced hands-on Python and SQL skills, with experience building analytical tools, automated reports, data pipelines, dashboards, or quantitative models.
• Strong quantitative foundation, including experience with stress testing, scenario analysis, statistical modeling, portfolio risk measurement, cash-flow modeling, optimization, or capital/liquidity analytics.
• Ability to work with large, imperfect, multi-source datasets and reconcile analysis to investment, accounting, statutory, or risk reporting sources.
• Strong communication skills, including the ability to explain technical analysis clearly to investments, risk, finance, technology, and senior stakeholders.
• Results-oriented, intellectually curious, self-motivated, collaborative, and comfortable working in a fast-paced environment with evolving priorities.

• Financial analysis, financial modeling, portfolio management, portfolio risk, insurance capital, liquidity, ALM, rating-agency capital models, or statutory accounting.
• Risk appetite dashboards, limit framework, stress-testing frameworks, or Board/senior-management risk reporting.
• Use of AI, large language models, or agentic tools for investment research, risk surveillance, reporting automation, document intelligence, code generation, or data quality workflows.
• Model risk management, AI governance, data controls, auditability, and reproducibility in a regulated financial services environment.