Machine Learning PhD Internship

Job Description

About Company

Susquehanna (referred to as Susquehanna or SIG in the context) is a quantitative trading firm that operates at the intersection of data, algorithms, and financial markets. They leverage machine learning, data science, and cutting-edge research to solve high-impact problems in quantitative trading and finance. The company is characterized by a collaborative, intellectually stimulating environment with global reach, and offers access to unparalleled financial data and computing resources.

Job Description, Detailed

This is a Machine Learning PhD Internship at Susquehanna, designed as a 10-week immersive experience.

1. Overview and Purpose:
• The internship is tailored for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.
• Interns will work on projects that closely mirror the challenges and workflows of Susquehanna’s full-time research team.
• The core objective is to apply technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna’s research and trading systems.
• Interns will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in areas ranging from predictive modeling to strategic execution.

2. Key Responsibilities and Expected Activities:
• Conduct research and develop ML models specifically designed to identify patterns within noisy, non-stationary financial data.
• Work directly with the Machine Learning team on real, impactful problems in quantitative trading and finance.
• Act as a bridge between cutting-edge ML research and practical implementation within the trading systems.
• Collaborate extensively with various stakeholders, including researchers, developers, and traders, to enhance existing models and explore novel algorithmic approaches.
• Design and run experiments utilizing the latest ML tools and frameworks.
• Receive one-on-one mentorship from experienced researchers and technologists.
• Participate in a comprehensive education program that includes deep dives into Susquehanna’s ML, quantitative analysis, and trading practices.
• Apply rigorous scientific methods to extract meaningful signals from complex datasets and contribute to the firm’s understanding of market behavior.
• Explore various facets of machine learning in quantitative finance, encompassing aspects like alpha generation, signal processing, model deployment, and risk-aware decision making.

3. Desired Qualifications and Skills:
• Currently pursuing a PhD in a highly relevant field such as Computer Science, Machine Learning, Statistics, Physics, or Applied Mathematics, or a closely related discipline.
• Demonstrated proven experience applying machine learning techniques in either a professional or academic setting.
• A strong publication record in top-tier machine learning conferences (e.g., NeurIPS, ICML, ICLR) is highly valued.
• Hands-on experience and proficiency with widely used machine learning frameworks, specifically PyTorch and TensorFlow.
• A deep interest in solving complex problems and a strong drive to innovate within a fast-paced, competitive environment.

4. Benefits of Joining:
• Opportunity to work with a world-class team of researchers and technologists.
• Access to unparalleled financial data and computing resources.
• The chance to make a direct and tangible impact on trading performance.
• Immersion in a collaborative, intellectually stimulating environment with global reach.

5. Compensation and Logistics:
• Interns will receive a weekly base salary of $6000 for the duration of the ten-week program.
• In addition to the salary, interns will also receive a signing bonus.
• Housing, breakfast and lunch, and other undisclosed perks will be provided.
• Recruiting for this position is scheduled to begin in July.
• Note for Recruiting Agencies: Agencies interested in partnership should contact `recruiting@sig.com`. Any resume or referral submitted without a signed agreement will not be eligible for an agency fee.