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PDT Partners

Quantitative asset management via algorithmic trading

Finance Associate

TreasuryConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • 2–4 years of professional experience in Finance, Treasury, Data Science, Management Information Systems, Accounting and Tax, or related fields.
  • Basic programming skills or experience with AI-assisted tools to automate and streamline workflows.
  • Strong analytical and quantitative skills.
  • Intellectual curiosity and eagerness to learn the business and understand the rationale behind processes.
  • Demonstrated diligence and thoroughness in delivering high-quality work.
  • Motivation to take on new challenges and persist in completing work.
  • Self-motivation to deliver high-quality work and identify opportunities for improvement.
  • Ability to communicate clearly and concisely in speech and writing.
  • Ability to collaborate and work effectively across teams.

Responsibilities

  • Develop broad expertise by rotating across treasury, finance, fund reporting, and tax compliance.
  • Support day-to-day FACT operations, including cash management, margin analysis, tax estimates, compliance reporting, and counterparty management.
  • Identify opportunities to streamline workflows and implement solutions by collaborating with internal operations development teams and leveraging data systems and AI tools.
  • Liaise with external service providers, such as prime brokers and accounting firms.
  • Lead or contribute to special projects and ad hoc analyses within the FACT team and across the firm.

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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