Machine Learning Researcher - PhD: 2027

SIG Susquehanna; New York (NY); On-site; USD 270,000 - 330,000; Full time

Job summary

Susquehanna is expanding its Machine Learning group in New York to hire a Machine Learning Researcher who will apply advanced ML to forecasting challenges, including time series and NLP, influencing trading strategies and decision-making.

You will design and run experiments, develop production-ready models, collaborate with researchers, traders, and engineers, and publish results. A PhD and 5+ years of deep learning experience and Python/C++ proficiency are preferred.

Qualifications

• PhD in computer science, machine learning, mathematics, physics, statistics, or related field.
• 5+ years of experience building impactful deep learning systems.
• Strong publication record in NeurIPS, ICML, or ICLR.
• Strong programming in Python and/or C++.
• Practical knowledge of ML libraries such as PyTorch or TensorFlow, especially in production environments.
• Hands-on experience applying deep learning on time series data.

Responsibilities

• Research and develop deep learning models to generate and enhance systematic trading signals.
• Collaborate with researchers, traders, and developers to improve alpha generation.
• Design and conduct experiments using modern ML frameworks to improve predictive signals.
• Extract actionable signals from complex datasets to understand market behavior.
• Translate research insights into production-ready models for live trading environments.
• Partner with engineering and trading teams to deploy, monitor, and iterate on models.

Skills

Python

C++

Deep learning

Time series

Experiment design

Collaboration

Education

PhD in CS/ML/related field

Tools

PyTorch

TensorFlow

Job description

Overview

Susquehanna is expanding the Machine Learning group and seeking exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural language understanding, and more. Your work will directly influence our trading strategies and decision-making processes. This is a unique opportunity to work at the intersection of cutting-edge research and real-world impact, leveraging one of the highest-quality financial datasets in the industry.

We’re looking for research scientists with a proven track record of applying deep learning to solve complex, high-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a passion for experimenting with model architectures, feature engineering, and hyperparameter tuning to produce resilient and high-performing models.

What you\'ll do

• Research and develop deep learning models to generate and enhance systematic trading signals and strategies across asset classes.


• Collaborate closely with researchers, traders, and developers to improve alpha generation and identify new algorithmic trading strategies.


• Design and conduct rigorous experiments using modern machine learning frameworks to improve predictive signals and overall trading performance.


• Apply scientific methods to extract actionable signals from complex datasets, deepening the understanding of market behavior.


• Translate research insights into production-ready models that can be implemented, tested, and validated in live trading environments.


• Partner with engineering and trading teams to deploy, monitor, and iterate on models that drive trading decisions and execution outcomes.

What we\'re looking for

• PhD in computer science, machine learning, mathematics, physics, statistics, or a related field


• Strong track record of applying ML in academic or industry settings, with 5+ years of experience building impactful deep learning systems


• A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR


• Strong programming skills in Python and/or C++


• Practical knowledge of ML libraries and frameworks, such as PyTorch or TensorFlow, especially in production environments


• Hands-on experience applying deep learning on time series data


• Strong foundation in mathematics, statistics, and algorithm design


• Excellent problem-solving skills with a creative, research-driven mindset


• Demonstrated ability to work collaboratively in team-oriented environments


• A passion for solving complex problems and a drive to innovate in a fast-paced, competitive environment


• Visa sponsorship is available for this position

The annual base pay for this role is $300,000. Susquehanna considers factors such as scope and responsibilities of the position, work experience, education/training, key skills, as well as market and organizational considerations when extending an offer.

What we offer

• Collaborate with a world-class team of researchers, engineers, and traders


• Gain access to best-in-class financial data and high-performance computing resources


• Directly impact real-time trading performance through your work


• Thrive in a collaborative, intellectually rigorous environment with a global footprint

About Susquehanna

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.