Athene

Associate, AI Solutions & Quantitative Strategist

New York, New York

Sponsorship not specified$175k-$200kDetected 21 days ago

PythonVector DatabasesMachine LearningData EngineeringLLMsRAGRecruitingResearchLeadershipCommunicationCollaborationUnderwriting

About the role

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.
This is not a direct investing role; but focused on enhancing the Hybrid business through AI and technology enablement to make better investment decisions.

Develop proof-of-concepts and practical prototypes to demonstrate value and accelerate buy-in from stakeholders.
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 building and deploying LLM-based applications (prompt engineering, RAG, agent frameworks such as LangChain or similar)
Our breadth and scale enable us to deliver capital for even the largest projects - and our small firm mindset ensures we will be a thoughtful and dedicated partner to these organizations.
We are committed to helping them build stronger businesses.
Lead responsibly
Drive collaboration

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
Experience with credit analysis workflows: capital structure modeling, comparable company analysis, scenario analysis

Position Overview
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 is not a direct investing role
Immediate or near-term start date strongly preferred.
Bachelor's degree with a strong record of academic achievement
advanced degree a plus.

$175,000 - $200,000 Apollo Global Management, Inc. (together with its subsidiaries and affiliates) is committed to championing opportunity.
The contents of the qualifications and experience section of this job description are a guideline only. If an applicant can otherwise demonstrate their suitability for the role they will be considered.
T he base salary range for this position is listed above.
This position is also eligible for a discretionary annual bonus based on personal, team, and Firm performance.
Compensation ranges are based on several factors including job function, level, and geographic location.
Final offer amounts are determined by multiple factors including candidate experience and expertise, and may vary from the amounts listed here.

Apollo relies on its people to keep it a leader in alternative investment management, and the firm's benefit programs are crafted to offer meaningful coverage for both you and your family.
The leading provider of retirement income solutions to institutions, companies, and individuals.
Evaluate and pilot external AI vendors and service providers, including conducting structured testing, cost-benefit analysis, security/compliance coordination and performance assessments.
Through Athene, our retirement services business, we specialize in helping clients achieve financial security by providing a suite of retirement savings products and acting as a solutions provider to institutions.
Stay current on developments in AI, machine learning and emerging technologies, bringing relevant insights and opportunities to the Apollo Hybrid platform.

in employment or recruitment based on race, color, religion, gender, national origin, veteran status, disability, age, citizenship, marital or domestic/civil partnership status, sexual orientation, gender identity or exp

This listing is sourced directly from Athene's careers page and normalized into a canonical job model.