Inactive
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PDT Partners

Quantitative asset management via algorithmic trading

Summer 2025 Software Engineering Internship

Backend Engineering +1Posted on Jul 7, 2024
Internship · Summer 2025New York, NY, USA

About the Job

Requirements

  • Currently pursuing Bachelor's or Graduate degree in a rigorous Computer Science, Computer Engineering, or other highly-technical field of study
  • Interest in working in a world-class, professional environment
  • Smart, fast-learner, intellectually curious, problem-solving approach
  • Can-do attitude, with sense of urgency
  • Strong verbal and written communication skills
  • Committed to improvement and keen to apply constructive feedback
  • Excellent academic background from a rigorous and challenging computer science program

Responsibilities

  • Work closely with expert developers on technically-challenging projects to design, develop, debug, and test our software components for large handling of financial data, real-time events, and batch processing
  • Work on projects that require client and server-side implementation
  • Face problems that don't have well-defined solutions - creativity is essential to come up with the best possible answers, including ones that explore new technologies
  • Learn about the financial markets, risk metrics, and portfolio management
  • Navigate various trading technologies like FIX messaging and order management systems
  • Construct, maintain, and analyze large-scale data sets
  • Learn to correctly apply new idioms, techniques, and algorithms in the following areas: Program correctness (resource management, exception safety, reentrancy/thread safety), Maintainability (portability, good coding practices, adherence to coding standards, unit testing, documentation), Efficiency (optimal data structures/algorithms, understanding of high-/low- level implications and trade-offs in design choices, parallelization)

About the Company

PDT Partners

Quantitative asset management via algorithmic trading

PDT Partners uses quantitative models to identify market inefficiencies and predict price movements for institutional clients through algorithmic trading. It analyzes large market datasets to find patterns and executes trades with automated strategies that run with precision. Differentiators include a long history since the 1990s, emphasis on empirical validation and scientific research, and a collaborative culture that vets ideas before implementation. The goal is to deliver consistent investment returns by systematically exploiting market inefficiencies through data-driven trading.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
New York City, New York
Founded
1993

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