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Execution Research Lead

at Durlston Partners

Back to all Python jobs
Durlston Partners logo
Recruitment Agencies

Execution Research Lead

at Durlston Partners

ExperiencedNo visa sponsorshippython

Posted 7 hours ago

0 clicks

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
Not specified

This role involves leading the execution research efforts at a top Crypto Quant fund, focusing on developing and optimizing execution strategies and infrastructure. It offers a unique opportunity to be the inaugural hire in this domain and shape the execution approach from the ground up.

A top Crypto Quant fund (backed by TradFi) is looking to hire a Quantitative Researcher to spearhead their Execution research function. This is a unique opportunity to be the first dedicated hire in this area, with the potential to shape and lead execution strategies and infrastructure.

Role Overview

As the Execution Quantitative Researcher, you will play a pivotal role in establishing and advancing execution research efforts. This is an exciting opportunity to be the inaugural hire in this domain, allowing you to define and lead our execution strategies from the ground up and learn on the job.

Key Responsibilities

  • Strategy Development: Create and enhance execution strategies aimed at capitalising on new alpha signals over various time frames, ranging from seconds to hours.
  • Slippage Minimisation: Optimise order placement and scheduling techniques to effectively reduce slippage during trades.
  • Market Impact Modeling: Develop comprehensive market impact models and seamlessly integrate them into the portfolio optimisation framework.
  • Backtesting Validation: Leverage internal trading data to validate and improve backtesting engines, ensuring robust performance analysis.
  • Collaborative Research: Work closely with fellow researchers to contribute to the overall development of trading strategies and methodologies

Qualifications and Skills

  • 2-8 years in Quant trading and Execution Research
  • Strong background in market microstructure analysis, transaction cost analysis (TCA), and simulator design
  • Proficient in Python; C++ knowledge is a plus
  • Familiarity with utility function design, rules-based logic for order execution, and multi-period optimization preferred
  • Advanced degree in a quantitative field (e.g., Computer Science, Mathematics, Physics)
  • Crypto trading experience is a plus but not required

Execution Research Lead

at Durlston Partners

Back to all Python jobs
Durlston Partners logo
Recruitment Agencies

Execution Research Lead

at Durlston Partners

ExperiencedNo visa sponsorshippython

Posted 7 hours ago

0 clicks

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
Not specified

This role involves leading the execution research efforts at a top Crypto Quant fund, focusing on developing and optimizing execution strategies and infrastructure. It offers a unique opportunity to be the inaugural hire in this domain and shape the execution approach from the ground up.

A top Crypto Quant fund (backed by TradFi) is looking to hire a Quantitative Researcher to spearhead their Execution research function. This is a unique opportunity to be the first dedicated hire in this area, with the potential to shape and lead execution strategies and infrastructure.

Role Overview

As the Execution Quantitative Researcher, you will play a pivotal role in establishing and advancing execution research efforts. This is an exciting opportunity to be the inaugural hire in this domain, allowing you to define and lead our execution strategies from the ground up and learn on the job.

Key Responsibilities

  • Strategy Development: Create and enhance execution strategies aimed at capitalising on new alpha signals over various time frames, ranging from seconds to hours.
  • Slippage Minimisation: Optimise order placement and scheduling techniques to effectively reduce slippage during trades.
  • Market Impact Modeling: Develop comprehensive market impact models and seamlessly integrate them into the portfolio optimisation framework.
  • Backtesting Validation: Leverage internal trading data to validate and improve backtesting engines, ensuring robust performance analysis.
  • Collaborative Research: Work closely with fellow researchers to contribute to the overall development of trading strategies and methodologies

Qualifications and Skills

  • 2-8 years in Quant trading and Execution Research
  • Strong background in market microstructure analysis, transaction cost analysis (TCA), and simulator design
  • Proficient in Python; C++ knowledge is a plus
  • Familiarity with utility function design, rules-based logic for order execution, and multi-period optimization preferred
  • Advanced degree in a quantitative field (e.g., Computer Science, Mathematics, Physics)
  • Crypto trading experience is a plus but not required