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Full-Time

Algorithm Developer – 2025 Grads

Quant Researcher

Confirmed live in the last 24 hours

Hudson River Trading

Hudson River Trading

501-1,000 employees

Algorithmic trading firm for institutional clients

Fintech
Quantitative Finance
Financial Services

Compensation Overview

$175k - $250kAnnually

+ Sign-on Bonus + Performance Bonus

Entry

New York, NY, USA

Category
Algorithm Development
Quantitative Research
Quantitative Finance
Required Skills
Python
R
MATLAB
Pandas
NumPy
C/C++
Data Analysis
Requirements
  • You are a full-time undergraduate or masters student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2025
  • Experience programming in Python and/or C++
  • Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
  • A passion for applying quantitative models and technology toward solving real-world problems
  • Brilliant analytical and problem-solving skills
  • Ability to work creatively and independently on long-term technical problems
Responsibilities
  • Algorithm Developers are responsible for building and maintaining the models that drive our trading.
  • A typical day involves applying rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models.
  • In this role, you will work alongside fellow Algorithm Developers and Software Engineers to research, develop, and test novel order execution and model training methods to increase trading efficiency.
  • This will involve running models live on our high-performance trading infrastructure and analyzing daily performance to maintain ongoing profitability.

Hudson River Trading focuses on algorithmic trading, utilizing advanced mathematical models and computing systems to make trading decisions in financial markets. The firm develops proprietary trading algorithms that analyze large volumes of market data to identify and execute trades at high speeds, often within milliseconds. Unlike many competitors, HRT emphasizes a scientific approach and invests significantly in research and development to enhance its trading strategies. The company's goal is to serve institutional clients, such as hedge funds and investment banks, by providing efficient high-frequency trading solutions across global markets.

Company Stage

N/A

Total Funding

$630M

Headquarters

New York City, New York

Founded

2002

Simplify Jobs

Simplify's Take

What believers are saying

  • Working at HRT offers exposure to cutting-edge technology and advanced mathematical models, providing a stimulating environment for researchers and developers.
  • The firm's global operations provide opportunities for international collaboration and career growth in major financial markets.
  • HRT's focus on high-frequency trading strategies allows employees to be at the forefront of financial innovation and market dynamics.

What critics are saying

  • The highly competitive nature of the algorithmic trading industry requires constant innovation to stay ahead, which can be demanding and stressful.
  • Regulatory changes in financial markets could impact HRT's trading strategies and profitability.

What makes Hudson River Trading unique

  • Hudson River Trading's scientific approach to algorithmic trading, leveraging advanced mathematical models and sophisticated computing systems, sets it apart from traditional trading firms.
  • The firm's global presence in key financial hubs allows it to capitalize on opportunities across various asset classes and markets, unlike competitors with a more localized focus.
  • HRT's heavy investment in research and development ensures continuous improvement of its proprietary trading algorithms, maintaining a competitive edge in the high-frequency trading sector.

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Benefits

Dental, Vision, Disability, Health, Life, and Supplemental Life Insurance

Flexible Spending Account

Health Savings Account

401(k)

Paid Time Off

Free lunch or snacks

Gym membership