Associate, Quantitative Strategist

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Position Overview Apollo's Hybrid team manages ~$100B in AUM covering both public and private assets across the capital structure. The team operates a research-intensive investment process - from screening public bonds and leveraged loans against quantitative return targets, through originating private transactions, to complex structured deals. This role will be responsible for helping to shape and execute Hybrid's AI and technology strategy, acting as a catalyst to transform how the business operates, sources opportunities, underwrites investments, manages portfolios and engages with internal and external stakeholders. The position will serve as a bridge between the Hybrid investment teams and Apollo's Apollo Global Investment Insights ("GII") Quant Team, ensuring that AI initiatives are practical, high-impact and embedded into day-to-day workflows. The AI Lead will drive engagement across the Hybrid platform, identify and prioritize use cases, develop and pilot new tools, evaluate third-party vendors, and provide regular updates to leadership on progress and impact. The ideal candidate will be entrepreneurial, highly collaborative, and passionate about leveraging AI to create durable competitive advantage. This is not a direct investing role; but focused on enhancing the Hybrid business through AI and technology enablement to make better investment decisions. Immediate or near-term start date strongly preferred. Primary Responsibilities: Drive the development and execution of Hybrid's AI roadmap in close partnership with Hybrid leadership, the Hybrid research/investment team and Apollo Global Investment Insight Quant Team. Act as a transformational agent across the Hybrid platform, identifying high-impact AI use cases across sourcing, diligence, underwriting, portfolio management, reporting and internal operations. Encourage adoption and engagement across investment teams by conducting teach-ins, training sessions, workshops and targeted working sessions to embed AI tools into day-to-day workflows. Partner with Apollo engineering and data teams to scope, prioritize, design, test and deploy new AI-enabled tools and enhancements tailored to Apollo Hybrid's team needs. Evaluate and pilot external AI vendors and service providers, including conducting structured testing, cost-benefit analysis, security/compliance coordination and performance assessments. Develop proof-of-concepts and practical prototypes to demonstrate value and accelerate buy-in from stakeholders. Serve as a liaison between Hybrid investment professionals, Apollo Global Investment Insight Quant Team and technology teams to translate business needs into technical requirements and ensure solutions are practical and scalable. Coordinate across Apollo functions (legal, compliance, risk, information security, finance, human capital) to ensure AI initiatives are implemented in alignment with firm-wide standards and governance. Stay current on developments in AI, machine learning and emerging technologies, bringing relevant insights and opportunities to the Apollo Hybrid platform. Key areas of focus include: investment research automation, screening / portfolio monitoring tools and investment team workflow / process automation Qualifications & Experience Bachelor's degree with a strong record of academic achievement; advanced degree a plus. 3+ years of experience in quantitative finance, data engineering, or applied AI/ML in an investment context Experience with financial data APIs (Bloomberg, ICE, Refinitiv) and structured/unstructured data pipelines Familiarity with credit markets - leveraged loans, high yield bonds, or structured credit - sufficient to understand the investment workflow including sourcing, diligence, underwriting and portfolio management and ability to build relevant tools Experience with credit analysis workflows: capital structure modeling, comparable company analysis, scenario analysis Experience building and deploying LLM-based applications (prompt engineering, RAG, agent frameworks such as LangChain or similar) Familiarity with vector databases, fine-tuning workflows, or evaluation frameworks for LLM outputs Ability to work directly with investment professionals to translate qualitative use cases into working quantitative tools High attention to detail and strong communication skills - outputs will be used in live investment decisions Preferred Prior experience in an investment bank, hedge fund, credit fund, or similar environment Exposure to deal workflow systems (DealCloud or equivalent) and portfolio management platforms Strong Python skills About Apollo Apollo is a high-growth, global alternative asset manager. In our asset management business, we seek to provide our clients excess return at every point along the risk-reward spectrum from investment grade credit to private equity. For more than three decades, our investing expertise across our fully integrated platform has served the financial return needs of our

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