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Head of Execution Technology

Remote:

Full Remote

Contract:

Full time

Work from:

France

Offer summary

Qualifications:

Bachelor’s degree in Engineering, Computer Science or related field, Strong skills in C++ / Python and/or machine learning systems.

Key responsabilities:

Manage a team of 5 to 10 and report to the Head of Trading Execution Technology
Maintain and develop feedhandlers, execution libraries, and predictors based on machine learning techniques
Optimize latency from real-time data reception to order submission
Compile data for transaction cost analysis metrics

Capital Fund Management (CFM) Investment Management SME http://www.cfm.fr/

201 - 500 Employees

See more Capital Fund Management (CFM) offers

Job description

In close collaboration with quantitative research team on execution strategies and trading application development team, the Trading Core & Model Technology team is looking for:

A manager

You will manage a 5 to 10 people
You will report to the Head of Trading & Execution Technology

the team’s mission is to maintain and develop:

Feedhandlers enabling real-time distribution, with low latency, to various company applications.
Common execution libraries used by applications and tick by tick execution strategy simulators (C++):
- Order flow management.
- Network and processor optimized code enabling high-volume, low-latency tick by tick data delivery to trading applications.
Predictors based on machine learning techniques:
- Machine learning pipeline for execution signals
- Improvement of machine learning based predictors used in execution strategies.

- Industrialization of data engineering and machine learning pipelines

- Construction and maintenance of the technical infrastructure used for execution research (C++, Python, petabytes of data)

- Close collaboration with quantitative researchers to create high-quality solutions.

- Data collection for Calculation and distribution of transaction cost analysis metrics (C++, Python, SQL, Tableau)

- Automated analysis reports for execution research, portfolio investor relation, and compliance

The team is also responsible for optimizing latency from real-time reception to order submission.

Bachelor’s degree in Engineering, Computer Science or a related field.
Strong team management and project coordination skills.
Ability to collaborate closely with quantitative researchers and understand their needs.
Strong skills in C++ / Python and/or machine learning systems

Your plusses:

Experience in developing high-performance, low latency trading applications.
Knowledge of execution libraries and execution strategy simulators.
Understanding of order flow management concepts and real-time market data management.
Proficiency in SQL and data analysis tools such as tableau.