Quant jobs / Millennium

Data Scientist

A data science role on the Volatility Alpha Development team applying AI and ML to volatility forecasting, options pricing and signal generation. It also builds agentic research workflows for portfolio managers.

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.

Develop ML models for volatility forecasting and signals
Build accelerated research workflows using JAX and PyTorch
Design LangGraph agent workflows with evaluation and tracing
Build LLM-based decision support tools for investment teams
Maintain model monitoring, versioning and reproducibility

What they ask for

Required

Degree in a quantitative field
3+ years in a quantitative or data-driven financial environment
Strong Python
Kubernetes, Docker and Airflow
CI/CD
Options and derivatives knowledge

Preferred

C++, Java, Rust, Go or C#

Education: Bachelor's, Master's or PhD in computer science, engineering, maths, physics or a related quantitative field
Experience: 3+ years in a quantitative, engineering or data-driven financial services environment
Languages and tools: Python
JAX
PyTorch
C++
Java
Rust
Go
C#
Markets: options

How to prepare

Train a PyTorch or JAX model to forecast realised volatility
Build a small LangGraph agent with evaluation traces
Set up an Airflow pipeline with experiment tracking
Learn options pricing basics and implied volatility

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 Millennium’s site before applying: requirements, location and pay can change after we check them.

View the posting on Millennium’s site ↗

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