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Quant trader

Roles & Responsibilities

  • 5+ years of hands-on experience in quantitative trading or systematic strategy development
  • Strong foundation in mathematics, statistics, financial engineering, or a related quantitative field
  • Proficiency in programming languages such as Python, C++, or similar for research and live trading environments
  • Deep understanding of financial markets, derivatives, and market microstructure

Requirements:

  • Design, develop, and implement systematic quantitative trading strategies across relevant asset classes
  • Conduct in-depth quantitative research using statistical modeling, time-series analysis, and machine learning techniques
  • Build, test, and optimize backtesting frameworks to validate trading hypotheses
  • Deploy and monitor live trading strategies, ensuring performance stability and scalability

Job description

This role is for one of the Weekday's clients

Min Experience: 5 years

Location: Remote (India)

JobType: full-time

We are looking for an experienced Quant Trader to join a performance-driven trading team operating across global financial markets. This is a full-time remote opportunity (India) for professionals with 5+ years of experience in quantitative trading who excel at building data-driven, systematic strategies. In this role, you will research, design, and deploy algorithmic trading models using advanced statistical techniques and technology-driven execution systems. You will work at the intersection of quantitative research, market microstructure, and risk management, continuously optimizing strategies to adapt to evolving market dynamics. The ideal candidate thrives in fast-moving environments, demonstrates strong analytical rigor, and is motivated by measurable trading performance and innovation.

Requirements

Key Responsibilities

  • Design, develop, and implement systematic quantitative trading strategies across relevant asset classes.
  • Conduct in-depth quantitative research using statistical modeling, time-series analysis, and machine learning techniques.
  • Build, test, and optimize backtesting frameworks to validate trading hypotheses.
  • Deploy and monitor live trading strategies, ensuring performance stability and scalability.
  • Analyze execution quality, transaction costs, slippage, and liquidity conditions to enhance trade efficiency.
  • Develop and maintain risk management models to control volatility, drawdowns, and capital exposure.
  • Track and evaluate performance metrics such as Sharpe ratio, alpha generation, and portfolio risk indicators.
  • Collaborate with technology teams to improve trading infrastructure, automation, and data pipelines.
  • Continuously refine strategies based on market behavior, macroeconomic trends, and structural changes.
  • Maintain detailed documentation and reporting of strategy performance and improvements.

What Makes You a Great Fit

  • 5+ years of hands-on experience in quantitative trading or systematic strategy development.
  • Strong foundation in mathematics, statistics, financial engineering, or a related quantitative field.
  • Proficiency in programming languages such as Python, C++, or similar for research and live trading environments.
  • Deep understanding of financial markets, derivatives, and market microstructure.
  • Proven track record of building profitable and scalable algorithmic trading strategies.
  • Experience with backtesting tools, large datasets, and performance analytics frameworks.
  • Strong risk management mindset with disciplined capital allocation practices.
  • Ability to work independently in a remote setup while maintaining high accountability and performance standards.
  • High intellectual curiosity, strong problem-solving ability, and a continuous improvement mindset.

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