Quant jobs / MSCI

Senior Data Science Engineer

MSCI’s data-science engineering team puts AI into financial-data products and internal platforms. This role builds production NLP and language-model features with controls for quality, traceability and responsible use.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Build extraction, classification and retrieval components for financial data.
Integrate language-model services with existing platforms.
Evaluate outputs and monitor reliability after deployment.
Implement data-governance and model-audit controls.

What they ask for

Required

Python
Applied ML and NLP
LLM application development
Production delivery
Software testing
Data governance

Preferred

Azure or GCP
CI/CD tools

Education: Bachelor’s or master’s qualification in computing, mathematics, engineering or a related quantitative subject.
Experience: 4–7 years of professional work applying ML, developing AI systems or practising data science.
Languages and tools: Python
LangChain
LangGraph

How to prepare

Build a retrieval pipeline with measurable extraction accuracy.
Test for leakage and unsupported outputs in an LLM application.
Package an AI service with versioning and monitoring.

What to study

The NLP and ML Quant Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on MSCI’s site before applying: requirements, location and pay can change after we check them.

View the posting on MSCI’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with MSCI and doesn’t handle applications.