Jihed Kamkoum

Direct the effort to maintain and enhance the DRIVE trading application.

This application is widely used to run diverse trading algorithms like market making, Greek adjustment,

position clearing and high frequency trading for all BNP Paribas trading desks (EU, UK, USA and HK).

The application Kernel is written in C++ (boost and Ace as API frameworks), the trading GUI in JAVA (RCP and SWT) and some HF trading algorithms are in Python.

The maintenance process and enhancement tasks are mainly (90%) impacting the kernel part (C++).

Analyse, design, develop and test business improvement requests. Investigate technical production problems and provide prompt fixes.

Carry out the development of a major improvement on the Drive application architecture to enable it to run trading algorithms for more than 2000 underlyings. This major improvement impacts the GUI part (Java SWT) and the C++ part (trading algorithms and products loading).

Implement High Frequency trading algorithms with Python in order to trade future commodity spread products for UK trading desks. dashboard for a monitoring and quality assurance purposes. (Using Gmock/Gtest framework)

Implement from scratch a queue based multicast service for trades booking and negotiations between Sales and Traders (C++ , IBM MQ and MongoDb) .

Carry out the deployment of Big Data tools like Splunk, Kibana, Logstash and Elasticsearch to provide KPI information to traders and bugs early detection tools to trading support teams.

Carry out the implementation (from scratch) of a Market Access server (MAS).

MAS is written in C# .Net core 2 and uses a TCP implementation of the FIX protocol to connect with client applications.

MAS centralizes various services needed by both front office applications (trading tools…) and back office applications (Market abuse detection …)

Market data connectors, referential gathering, Order passing, feed replayers and pricing service are a glimpse of services provided by MAS.

Implement a bus based multicast service for market data using RabbitMQ and Kafka.

Implement a real time implied price calculator which uses location and time spread to compute a best price.

Carry out the implementation of market data and order passing connectors for various Gaz and Energy market places like ICE, Nordpool, Trayport and Epex.

Actively participating on pull request validation , documentation and production monitoring/support .

Lead the implement a monitoring and administration dashboard for MAS using Angular.

Continuously working on improving the team’s tools (VSTS) and scripts (PowerShell) used in daily development tasks.

Direct the effort to maintain and enhance the DRIVE trading application.

This application is widely used to run diverse trading algorithms like market making, Greek adjustment,

position clearing and high frequency trading for all BNP Paribas trading desks (EU, UK, USA and HK).

The application Kernel is written in C++ (boost and Ace as API frameworks), the trading GUI in JAVA (RCP and SWT) and some HF trading algorithms are in Python.

The maintenance process and enhancement tasks are mainly (90%) impacting the kernel part (C++).

Analyse, design, develop and test business improvement requests. Investigate technical production problems and provide prompt fixes.

Carry out the development of a major improvement on the Drive application architecture to enable it to run trading algorithms for more than 2000 underlyings. This major improvement impacts the GUI part (Java SWT) and the C++ part (trading algorithms and products loading).

Implement High Frequency trading algorithms with Python in order to trade future commodity spread products for UK trading desks. dashboard for a monitoring and quality assurance purposes. (Using Gmock/Gtest framework)

Carry out the deployment of Big Data tools like Splunk, Kibana, Logstash and Elasticsearch to provide KPI information to traders and bugs early detection tools to trading support teams.