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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

Your missions

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.