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Quantitative Researcher - Statistical Modeling

Quantitative Researcher - Statistical Modeling

SKS EnterprisesGurugram
30+ days ago
Job description

Position Name : Quant Researcher.

Location : Gurgaon.

Experience Range : 2+years.

Role Overview :

We are seeking a highly motivated and analytical Quantitative Trader to join our dynamic trading team.

In this role, you will design, implement, and execute data-driven trading strategies across various asset classes.

Youll work in a fast-paced, collaborative environment where creativity, precision, and agility are key.

Key Responsibilities :

  • Develop, backtest, and deploy algorithmic trading strategies using historical and real-time market data.
  • Monitor and manage the performance of live strategies; optimize and refine models based on results and market behavior.
  • Conduct in-depth quantitative research to discover alpha signals and improve existing models.
  • Collaborate with developers and researchers to enhance trading infrastructure, data pipelines, and execution systems.
  • Analyze risk and maintain robust risk management practices in all aspects of trading.
  • Stay updated with market trends, regulatory changes, and trading technologies.

Requirements :

  • Bachelors, Masters, or Ph.D. in a quantitative field such as Mathematics, Statistics, Computer Science, Physics, or Engineering.
  • 2+ years of experience in a quantitative trading or research role (internships also considered for junior roles).
  • Strong programming skills in Python, C++, or Java (Python preferred).
  • Experience with data analysis, statistical modeling, and backtesting frameworks.
  • Solid understanding of financial markets, trading instruments, and market microstructure.
  • Familiarity with tools such as Pandas, NumPy, scikit-learn, KDB+ / q, or similar.
  • Excellent problem-solving skills, attention to detail, and ability to work under pressure.
  • Preferred Qualifications :

  • Experience in high-frequency or low-latency trading environments.
  • Knowledge of machine learning or deep learning techniques.
  • Exposure to cryptocurrencies, futures, options, or other derivatives.
  • Familiarity with FIX protocol or working with trading APIs.
  • ref : hirist.tech)

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