Quantitative Research Intern - AI for Investment Research

lombardodier; Genf; On-site; CHF 22,000 - 31,000; Part time

Job summary

Lombard Odier is seeking a Quantitative Research Intern to develop AI-driven research tools for equity and fixed income strategies. You will work with researchers, PMs, and analysts to apply LLMs to investment problems.

The role focuses on building AI-enabled research signals, summarizing unstructured data, and evaluating insights for investment decision-making within a leading wealth and asset manager.

Qualifications

• Knowledge of equity and/or fixed income investing.
• Experience with financial datasets such as fundamentals, transcripts, credit metrics.
• Exposure to ML/NLP, LLM frameworks and AI tooling.
• Experience building RAG systems, AI agents, or evaluation frameworks.
• Familiarity with cloud AI platforms and APIs.
• Prior research in ML, NLP, or applied AI.

Responsibilities

• Develop AI- and LLM-based tools to support investment research.
• Build systems to extract, summarize, and analyse information from filings, transcripts, and data.
• Design and evaluate retrieval-augmented generation workflows for research apps.
• Explore foundation models to improve information discovery and knowledge management.
• Apply ML techniques to structured and unstructured datasets.
• Prototype tools linking internal databases with research repositories.
• Present findings through research reports to investment professionals.

Skills

Equity investing

Fixed income investing

Portfolio construction

Risk management

Quantitative analysis

NLP / ML foundations

Education

Bachelor’s or Master’s in Finance/CS/Data Science

Tools

LangChain

LlamaIndex

LangGraph

Job description

A career at Lombard Odier means working for a renowned global wealth and asset manager, with a strong focus on sustainable investing. An innovative bank of choice for private and institutional clients, our independently owned Firm is one of the best-capitalised banking groups in the world, managing close to CHF 300 billion and operating from over 25 offices across 4 continents.

With a history spanning over 230 years, Lombard Odier is an investment house providing a comprehensive offering of discretionary and advisory portfolio management, wealth services and custody. We also offer asset management services and investment strategies through Lombard Odier Investment Managers and provide advanced banking technology to other financial institutions.

\"Rethink Everything\" is our philosophy - it is at the heart of everything we do. We have grown stronger through more than 40 financial crises by rethinking the world around us to provide a fresh investment perspective for our clients.

Lombard Odier Investment Managers (\"LOIM\") is the asset management business of the Lombard Odier Group. In order to strengthen our Investment team, we are looking for a:

Quantitative Research Intern - AI for Investment Research

We are seeking a highly motivated Quantitative Research Intern to help develop AI-driven research tools and investment insights across equity and fixed income investment strategies, including both long-only and long-short portfolios.

The successful candidate will work closely with quantitative researchers, portfolio managers, and investment analysts to explore how Large Language Models (LLMs) and modern machine learning techniques can enhance the investment research process. This internship provides an opportunity to work on cutting-edge applications of AI in asset management, ranging from company and issuer analysis to the creation of novel investment signals derived from structured and unstructured data.

The role is research-oriented, hands-on, and ideal for candidates with a strong quantitative background who are excited about applying frontier AI technologies to real-world investment problems.

YOUR ROLE

As a Quantitative Research Intern, you will:

• Develop AI- and LLM-based tools to support investment research and decision-making.
• Build systems that extract, summarize, and analyse information from corporate filings, earnings calls, credit research, central bank communications, news, and other unstructured datasets.
• Design and evaluate retrieval-augmented generation (RAG) and agentic AI workflows for investment research applications.
• Explore the use of foundation models to improve information discovery, monitoring, and knowledge management across investment teams.
• Apply statistical and machine learning techniques to structured financial, macroeconomic, and market datasets.
• Assist in developing novel research signals and indicators derived from textual, alternative, and market data sources.
• Prototype tools that integrate internal databases, research repositories, and external data providers.
• Evaluate the robustness, reliability, and investment relevance of AI-generated insights.
• Present findings through research reports and presentations to investment professionals.

YOUR PROFILE

• Knowledge of equity and/or fixed income investing.
• Familiarity with portfolio construction, risk management, and systematic investment processes.
• Experience working with financial datasets such as company fundamentals, earnings transcripts, credit metrics, bond market data, analyst estimates, or macroeconomic data.
• Experience with LLM frameworks such as LangChain, LangGraph, LlamaIndex, or similar tools.
• Experience building RAG systems, AI agents, or evaluation frameworks.
• Familiarity with cloud-based AI platforms and APIs.
• Prior research experience in machine learning, NLP, or applied AI.

Example Projects

• Developing an AI-powered research assistant capable of analysing company filings, earnings transcripts, credit research reports, and internal investment documents.
• Building systems that identify and summarize material changes in corporate fundamentals, credit quality, and macroeconomic conditions.
• Creating novel textual and alternative-data signals for equity and fixed income investment strategies.
• Designing multi-agent workflows that automate parts of the investment research process across long-only and long-short portfolios.
• Evaluating the effectiveness of AI-generated insights relative to traditional quantitative signals and research methods.
• Building natural language interfaces that allow investment professionals to query internal databases, market data, and research repositories.

Our Maison's DNA is defined by five core values. Excellence drives us to be the best at what we do, while Innovation fuels our progress. Respect underpins every interaction, and Integrity shapes our actions. Together, we are One Team , united in serving our clients with unwavering dedication.

As a responsible and supportive employer, we pro