Quantitative Researcher

Venture Search

Singapore

On-site

SGD 150,000 - 230,000

Full time

21 hours ago
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Job summary

Venture Search in Singapore is seeking an Equities Quantitative Researcher to join its MFT-focused research team. You will work with portfolio managers, researchers and engineers to develop predictive signals and translate research into live systematic trading strategies.

The role offers exposure to the full research lifecycle, from hypothesis generation and modelling through backtesting, implementation and ongoing strategy improvement in a collaborative environment.

Qualifications

  • 3+ years of quantitative research experience within a systematic hedge fund or leading quant team.
  • Strong background in equities and medium-frequency systematic strategies.
  • Excellent foundations in statistics, mathematics, ML or econometrics.
  • Strong Python programming skills and experience working with large datasets.
  • Demonstrable ability to develop predictive signals and translate research into actionable trading strategies.

Responsibilities

  • Research and develop alpha signals for systematic equity strategies at medium frequency.
  • Analyse large financial datasets to identify predictive patterns and market inefficiencies.
  • Build and validate statistical models, trading signals and portfolio construction methodologies.
  • Conduct rigorous backtesting and performance attribution to assess signal robustness.
  • Collaborate with portfolio managers and engineers to implement and enhance live trading strategies.
  • Monitor strategy performance and identify opportunities to improve returns and risk efficiency.

Skills

Python programming
Statistics
Machine learning
Econometrics
Data analysis

Tools

Python

Job description

Equities Quantitative Researcher – MFT | Systematic Hedge Fund

Description:

Our client is a leading quantitative hedge fund with a strong track record in systematic investing across equities and futures. The firm combines rigorous quantitative research, sophisticated technology and a highly collaborative investment culture to develop and deploy systematic strategies across global markets.

The firm is looking to hire an Equities Quantitative Researcher with 3+ years of experience to join its Singapore team, focusing on medium-frequency trading (MFT).

The Opportunity:

This is an opportunity to work alongside high-calibre portfolio managers, researchers and engineers within a research-intensive investment environment. The successful candidate will contribute to the discovery of new alpha, developing predictive signals and translating quantitative research into live systematic trading strategies.

The role offers exposure to the full research lifecycle, from hypothesis generation and statistical modelling through to backtesting, implementation and ongoing strategy improvement.

Key Responsibilities:

  • Research and develop alpha signals for systematic equity strategies at medium frequency.
  • Analyse large financial datasets to identify predictive patterns and market inefficiencies.
  • Build and validate statistical models, trading signals and portfolio construction methodologies.
  • Conduct rigorous backtesting and performance attribution to assess signal robustness.
  • Collaborate with portfolio managers and engineers to implement and enhance live trading strategies.
  • Monitor strategy performance and identify opportunities to improve returns and risk efficiency.

Ideal Candidate:

  • 3+ years of quantitative research experience within a systematic hedge fund, proprietary trading firm or leading quantitative investment team.
  • Strong background in equities research and medium-frequency systematic strategies.
  • Excellent foundations in statistics, mathematics, machine learning or econometrics.
  • Strong Python programming skills and experience working with large datasets.
  • Demonstrable ability to develop predictive signals and translate research into actionable trading strategies.
  • Strong research ownership, intellectual curiosity and collaborative working style.
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