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Quantitative researcher (mid-frequency systematic equities)

Slough
EC1 Partners
Quantitative researcher
Posted: 13 May
Offer description

My client is seeking an experienced quantitative researcher to join a new team focused on

building a mid-frequency systematic equities trading system. The successful candidate will

work closely with the Senior Portfolio Manager to design and develop the strategy from the

ground up, taking a leading role in the research effort and the overall investment process.

This is a senior, leadership-oriented position that includes responsibility for shaping the

research agenda and supporting the growth of the team.


Core responsibilities


Research, build and maintain all aspects of the trading system, including alpha

research, signal construction and combination, portfolio construction, and trade

optimisation.


Build and maintain the quantitative research ecosystem, including data pipelines,

backtesting frameworks, and tools for evaluating model performance.


Implement robust logging, monitoring, and diagnostic processes for the trading

system, and drive timely investigation and remediation of issues.


Generate, test, and prioritise new research ideas to improve model performance and

robustness over time.


Contribute to the recruitment, mentoring, and development of junior team members,

fostering a rigorous and collaborative research culture.


Preferred Skills and Experience


Multiple years of experience working collaboratively on mid-frequency systematic

equities trading strategies.


Solid understanding of quantitative finance concepts, statistical analysis, and, ideally,

practical applications of machine learning.


Strong programming expertise in Python and related libraries (e.g. NumPy, pandas,

Polars, etc.).


Experience working with large, noisy datasets, including data cleaning, feature

engineering, and validation.


Masters or PhD in a quantitative subject


Creativity and out of the box thinking


Excellent analytical skills and a rigorous, detail-oriented approach to empirical

research.


Strong organizational skills with the ability to manage multiple projects concurrently.

High attention to detail and commitment to code quality.


Effective communication and collaboration skills; ability to work well within a team

environment.


Self-starter with a proactive approach to solving technical and operational

challenges.

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