AI Analyst

Millennium Management LLC; Hong Kong; On-site; HKD 900,000 - 1,500,000; Full time

Job summary

Millennium Management LLC is seeking an AI Analyst to design, implement, and scale AI applications across the fundamental equity investment process. You will work directly with portfolio managers, equity analysts, and technology partners to translate research needs into practical AI solutions.

The role combines deep buy-side equity-research experience with strong AI technical knowledge, focusing on improving research quality, speed, and decision-making while maintaining strong investment

Qualifications

• Minimum 5 years of buy-side experience as a fundamental equity analyst.
• Strong understanding of the end-to-end fundamental equity investment process, including idea generation, research, earnings analysis, catalysts, portfolio-management considerations, and risk.
• Deep practical knowledge of modern AI implementation and its applications in fundamental equity investing.
• Strong understanding of large language models, prompting, retrieval-augmented generation, embeddings, vector search, AI agents, document processing, structured-data extraction, and model evaluation.
• Ability to assess AI systems critically, including their limitations, hallucination risk, factual reliability, privacy and confidentiality considerations, security, and governance requirements.
• Experience translating business or investment workflows into technical requirements and collaborating effectively with engineers, data scientists, and technology teams.
• Excellent written and verbal communication skills, with the ability to explain technical concepts clearly to investment and senior-management audiences.
• Professional fluency in English and Mandarin.

Responsibilities

• Translate fundamental equity-research needs into clearly defined AI use cases and measurable objectives.
• Partner with portfolio managers and analysts to improve workflows across research, earnings prep, and knowledge management.
• Evaluate and implement AI-enabled research workflows, including LLMs, retrieval augmented generation, and document intelligence.
• Assess AI models, vendors, platforms, and tools for relevance to investing, considering accuracy, security, and cost.
• Develop rigorous evaluation frameworks for AI outputs, including attribution and factual accuracy.
• Work with engineers to translate investment requirements into deployable tools and data pipelines.
• Establish standards for responsible AI use in investment research and governance.
• Identify opportunities to improve efficiency without compromising investment judgment.
• Track AI and data infrastructure developments and translate them into durable capabilities.

Skills

Buy-side equity

Equity research process

AI systems

LLMs

Retrieval augmented generation

Embeddings

Vector search

Model evaluation

Data governance

Communication

English & Mandarin

Tools

Python

SQL

APIs

Data platforms

AI development frameworks

Job description

AI Analyst

Role: AI Analyst

About the job

About Millennium

Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.

Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.

About The Role

The Equity Management Team is seeking an AI Analyst to work directly with portfolio managers, fundamental equity analysts, investment professionals and technology partners. This newly created role will focus on identifying, designing, implementing, and scaling high-value AI applications across the fundamental equity investment process.

The successful candidate will combine deep buy-side fundamental equity-research experience with strong technical knowledge of modern AI systems. They will bring practical judgment about where AI can materially improve research quality, speed, breadth, and decision-making—and where investment judgment and conventional analytical approaches should remain central.

Core Responsibilities

• Translate fundamental equity-research needs into clearly defined AI use cases, measurable objectives, and practical technical solutions.
• Partner with portfolio managers and analysts to improve workflows across company research, industry analysis, earnings preparation, document analysis, knowledge retrieval, data extraction, monitoring, and idea generation.
• Evaluate and help implement AI-enabled research workflows, including large-language-model applications, retrieval-augmented generation, agentic workflows, document intelligence, structured-data extraction, and internal knowledge systems.
• Assess AI models, vendors, platforms, and tools for relevance to fundamental equity investing, considering accuracy, robustness, security, usability, scalability, latency, and cost.
• Develop rigorous frameworks to evaluate AI outputs, including benchmarking, source attribution, factual accuracy, hallucination risk, workflow reliability, user adoption, and investment-process impact.
• Work closely with engineers, data teams, and technology stakeholders to translate investment requirements into deployable tools, APIs, data pipelines, and monitored applications.
• Establish practical standards for responsible AI use in investment research, including confidentiality, data governance, model-risk controls, appropriate human oversight, and documentation.
• Identify opportunities to improve the efficiency and consistency of research processes while preserving the quality of investment judgment and differentiated fundamental insight.
• Track relevant developments in AI, machine learning, data infrastructure, and investment technology, and translate the most relevant advances into durable capabilities for the Equity Management Team.

Qualifications / Skills Required

• Minimum 5 years of buy-side experience as a fundamental equity analyst.
• Strong understanding of the end-to-end fundamental equity investment process, including idea generation, research, earnings analysis, catalysts, portfolio-management considerations, and risk.
• Deep practical knowledge of modern AI implementation and its applications in fundamental equity investing.
• Strong understanding of large language models, prompting, retrieval-augmented generation, embeddings, vector search, AI agents, document processing, structured-data extraction, and model evaluation.
• Ability to assess AI systems critically, including their limitations, hallucination risk, factual reliability, privacy and confidentiality considerations, security, and governance requirements.
• Experience translating business or investment workflows into technical requirements and collaborating effectively with engineers, data scientists, and technology teams.
• Strong analytical judgment and the ability to distinguish high-value, scalable AI use cases from applications that do not justify their complexity or risk.
• Excellent written and verbal communication skills, with the ability to explain technical concepts clearly to investment and senior-management audiences.
• Professional fluency in English and Mandarin.

Preferred Qualifications

• Experience implementing AI, data, or technology products in a hedge fund or a similarly research-intensive environment.
• Hands-on proficiency with Python, SQL, APIs, data platforms, or AI-development frameworks.
• Experience evaluating and deploying LLM-enabled applications, retrieval systems, research copilots, agentic workflows, and enterprise knowledge-management tools.
• Experience working with structured and unstructured financial data, including filings, earnings-call transcripts, research documents, market data, alternative data, and news.
• Familiarity with data pipelines, cloud infrastructure, model monitoring, user-feedback loops, and production-quality application delivery.
• Experience establishing AI evaluation, testing, governance, or model-risk frameworks.
• Genuine intellectual curiosity about companies, industries, investing, and the evolving AI ecosystem.
• A practical, collaborative working style characterized by ownership, scientific rigor, clear communication, sound judgment, and a focus on delivering measurable value for investment professionals.