PhD ML Researcher: Time-Series & Trading Signals

Trading Interview; Pennsylvania; Hybrid; USD 180,000 - 230,000; Full time

Benefits offered by this job

Top-tier data access

High-performance computing resources

Impact on trading performance

Global footprint

Job summary

Susquehanna is expanding its Machine Learning group and seeks exceptional researchers to join as Machine Learning Researchers. You will apply advanced ML techniques to forecasting challenges including time series analysis and natural language understanding, influencing trading strategies and decision-making processes.

You will work at the intersection of cutting-edge research and real-world impact, leveraging top-tier datasets and high-performance computing resources to advance alpha generation

Qualifications

• PhD in computer science, machine learning, mathematics, physics, statistics, or a related field.
• Strong track record applying ML in academic or industry settings with 5+ years 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++.
• Hands-on experience applying deep learning on time series data.

Responsibilities

• 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 ML frameworks to improve predictive signals and trading performance.
• Apply scientific methods to extract actionable signals from complex datasets, deepening market understanding.

Skills

Deep learning

Time series

PyTorch

Python

Team collaboration

Education

PhD in CS/ML/Math/Physics

Tools

PyTorch

TensorFlow

Job description

Job Type Full-time

Posted 3 months ago

The role

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

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.

If you're a recruiting agency and want to partner with us, please reach out to [e-mail]. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

#LI-CR1

#LI-Onsite

• 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

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.

If you're a recruiting agency and want to partner with us, please reach out to [e-mail]. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

#LI-CR1

#LI-Onsite

This description was published by Susquehanna International Group (SIG). Applications are handled on their careers site: we are not the employer and cannot process them.

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