Finance Data Science Intern - Summer 2027

Lazard; New York (NY); On-site; USD 45,000 - 60,000; Full time

Job summary

Lazard is inviting a Data Scientist Summer Intern to join the AI & Data Group in New York City. The role focuses on analyzing large‑scale finance datasets and extracting insights to support Lazard’s advisory and asset management businesses.

You will work closely with data scientists, investment bankers and senior management, contributing to end‑to‑end data projects, from exploration to deployment, using Python, ML methods and ML frameworks.

Qualifications

• Bachelor's or higher in Data Science, Computer Science, Statistics, Quantitative Finance, Business Analytics, or equivalent.
• Strong programming skills in Python; object‑oriented programming experience preferred.
• Excellent knowledge of ML algorithms and solid statistical/econometric modeling skills.
• Ability to query and analyze data from large‑scale databases; big data engineering experience preferred.
• Experience with data visualization and communicating results to non‑technical audiences.
• Familiar with large language model frameworks (LLMs).
• Ability to work independently and in teams; strong interest in finance preferred.

Responsibilities

• Analyze large‑scale data sets in finance and extract value‑adding insights.
• Collaborate with data scientists, investment bankers, portfolio managers, and senior management across the Firm.
• Support development of AI and data‑driven solutions within Lazard's AI & Data Group.

Skills

Python

Object‑Oriented

Machine Learning

Statistics

Data Visualization

LLM Frameworks

Big Data

Data Querying

Finance Interest

Education

Bachelor's or higher in Data Science / CS / Statistics

Tools

SQL

Spark

Pandas

Job description

Lazard is inviting a Data Scientist Summer Intern to join the AI & Data Group in New York City. The role focuses on analyzing large‑scale finance datasets and extracting insights to support Lazard’s advisory and asset management businesses.

You will work closely with data scientists, investment bankers and senior management, contributing to end‑to‑end data projects, from exploration to deployment, using Python, ML methods and ML frameworks.