Quantitative Researcher

2 days ago

Greater Bengaluru Area, India Move37 Capital Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Quantitative Researcher (Hedge Fund)

Location: Bengaluru, India

Firm AUM: USD 500 million +

Experience: PhD (0–2 years post-graduation)

About the Role A fast-growing, London-headquartered hedge fund applying advanced machine-learning techniques to global markets, and managing over $500 million in assets, is seeking a PhD level quantitative researcher for its Bengaluru office.

The role involves assisting the Portfolio Manager in alpha research and leading the execution research to enhance trade implementation and reduce market impact. You will apply advanced statistical and machine-learning methods to large-scale financial datasets, contributing directly to the fund's systematic research and trading process.

Key Responsibilities

  • Support the Portfolio Manager in day-to-day quantitative research and data analysis.
  • Lead execution research initiatives:

o Analyse market microstructure and high-frequency futures data.

o Model slippage, transaction costs, and liquidity impact.

o Develop and back-test execution algorithms and order-scheduling models.

  • Monitor and evaluate execution performance metrics, generating actionable insights.
  • Maintain clear documentation and communicate findings to the investment team.

Ideal Background

  • PhD (or near completion) in Mathematics, Physics, Statistics, Econometrics, or a related quantitative discipline.
  • Strong grounding in probability and statistics.
  • Proficiency in Python or similar data-analysis languages.
  • Experience working with large, noisy datasets and performing numerical analysis.
  • Curiosity about financial markets, trading systems, and quantitative execution research.
  • Exposure to machine learning or stochastic modelling during doctoral research.
  • Excellent analytical reasoning, precision, and attention to detail.

Why Join Us

  • Collaborate directly with the Portfolio Manager in a cutting-edge, research-driven environment.
  • Apply advanced quantitative and machine-learning techniques to global financial markets.
  • Be part of a collaborative culture that values intellectual rigor, technical depth, and curiosity.

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