Senior Quantitative Trading Researcher – Equities Execution & Microstructure

Posted byDirectorWe're partnering with a top-tier investment firm to find a Senior Quantitative Strategist for their Singapore office. This is a highly visible role for a senior quant with deep expertise in equity market microstructure, execution analytics, and signal research, particularly in the context of institutional trading and transaction cost optimization.

The Opportunity

You'll join a team at the forefront of equity execution research, working closely with high-touch and low-touch trading desks and portfolio managers. This role offers the chance to take strategic ownership of equity strategy, where you'll be empowered to take initiative to help improve and drive strategy. Your primary responsibility will be to analyze and optimize execution strategies, develop pre- and post-trade models, and translate tick-level and intraday data into actionable insights and improvements across the firm’s trading platforms. You'll also leverage a breadth of experience across asset classes to help with the strategic development and direction of the team.

What You’ll Do:

Conduct deep-dive analyses into equity execution costs, market impact, and trade timing Build and refine transaction cost models and short-term trading signals Develop tools and dashboards for real-time execution monitoring and strategy evaluation Lead cross-functional projects with quants, traders, and PMs to assess and implement execution enhancements Work with tick-level, intraday, and real-time market data, applying advanced quantitative techniques Provide insight into market microstructure trends

Ideal Background:

8+ years in a quant or trading research role within buy-side or sell-side equities Strong working knowledge of equity market microstructure, algorithmic execution, and liquidity dynamics Direct experience designing or optimizing execution strategies, ideally within a systematic or semi-systematic environment, with a proven track record of taking initiative to drive strategic improvements Breadth of experience across asset classes to support strategic team development Proficient in Python, SQL, R, and ideally kdb+/Q Strong background working with tick-level data, particularly for signal generation or execution cost modeling Advanced academic background, ideally with a PhD in a quantitative field (, Mathematical Finance, Statistics, Econometrics) Publications or presentations in market microstructure, algorithmic trading, or high-frequency econometrics are a plus.