Quant jobs / Schonfeld

Quantitative Researcher – Machine Learning Alphas

A machine-learning-focused researcher on Schonfeld's Hong Kong systematic trading team, designing alphas for liquid markets. The work spans features, distributed research pipelines and deployment of signals.

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.

Engineer predictive features from high-frequency market data and alternative data
Build research pipelines on a compute cluster for tree-based, deep learning and NLP models
Prototype ML-driven alphas for cash equities and futures
Deploy signals with developers and improve them from live results

What they ask for

Required

Tree-based models, deep learning and NLP/LLMs
Probability and overfitting control
Python
Distributed compute experience
Alpha research track record
Communication

Preferred

C++ or similar

Education: MS or PhD in computer science, statistics, maths or a related field from a top university.
Experience: 5+ years of alpha research at a leading buy-side firm or global bank
Languages and tools: Python
C++
Markets: equities, futures

How to prepare

Train gradient-boosted models on intraday features with leakage-safe validation
Study overfitting control methods such as purged cross-validation and multiple-testing corrections
Build a distributed experiment pipeline for feature research
Learn to turn a prototype signal into a production-ready one

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

View the posting on Schonfeld’s site ↗

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