Machine Learning Researcher

Susquehanna International Group, LLP
United States
26 days ago
Apply on www.dice.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Algorithm Design C++ (Programming Language) Computer Programming Python (Programming Language) Machine Learning Systems Development Life Cycle Tensorflow Feature Engineering Pytorch Deep Learning Scikit Learn Information Technology
+1 more
Machine Learning Operations

Job description

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

  • Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and scalable deployment
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • Develop automation tools to streamline research and system development
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Partner with engineering teams to implement and test models in production environments

Requirements

  • 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

About the company

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.dice.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:42 min

Choosing specialized libraries beyond scikit-learn

Adrian Schmitt · LIVE

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · World Congress 2023

1:39 min

Fundamentals of tensors and the TensorFlow library

Håkan Silfvernagel · LIVE

3:23 min

Exploring specialized career paths within the data science ecosystem

Julian Joseph · LIVE

1:06 min

Compiling PyTorch environments for advanced time forecasting

Christoph Lohrmann Christoph Lohrmann +1 · World Congress 2026 Europe

3:14 min

Structuring career paths and localized data architectures

Ulrich Wurstbauer +1 · LIVE

Videos

See all

Related articles

See all