Weekday

Weekday

Weekday helps companies hire engineers who are vouched by other software engineers, enabling passive income for engineers. They offer services like drafting outreach messages, shortlisting candidates, and conducting reference checks. Backed by Y Combin...

Construction & Engineering
11-50
Founded 2020

Description

  • Design, develop, and maintain quantitative models for pricing, risk analysis, portfolio optimization, and algorithmic trading.
  • Implement high-performance, scalable solutions using Python as the primary programming language.
  • Build and enhance data pipelines for large-scale financial datasets, ensuring data accuracy, integrity, and performance.
  • Collaborate with quantitative researchers to translate mathematical and statistical models into efficient, maintainable code.
  • Optimize existing models and systems for speed, memory efficiency, and reliability.
  • Develop backtesting frameworks and simulation environments to evaluate trading strategies.
  • Integrate models into production systems and support deployment in live trading environments.
  • Conduct rigorous testing, validation, and documentation of quantitative models.
  • Contribute to architectural decisions, technology stack improvements, and mentor junior developers on coding, testing, and version control best practices.

Requirements

  • 5–7 years of professional experience in quantitative development, financial engineering, or a related domain.
  • Strong expertise in Python and scientific libraries such as NumPy, Pandas, and SciPy.
  • Solid understanding of object-oriented programming, design patterns, and clean code principles.
  • Experience working with large datasets and applying performance optimization techniques.
  • Strong knowledge of statistics, probability theory, linear algebra, and numerical methods.
  • Experience in financial markets, derivatives pricing, risk modeling, or algorithmic trading (highly desirable).
  • Familiarity with backtesting frameworks and time-series analysis.
  • Proficiency in SQL and experience with relational or time-series databases.
  • Experience with version control systems (e.g., Git) and CI/CD practices, with strong problem-solving and analytical skills.
  • Preferred: experience applying machine learning to financial data; exposure to distributed computing frameworks or cloud platforms; knowledge of C++ or other performance-oriented languages; advanced degree (Master’s or PhD) in Mathematics, Finance, Computer Science, Engineering, or a related quantitative field.

Interested in this position?

Apply directly on the company website

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