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Data Scientist Intern

Ref : JRQ$202-16801

Paris

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Job description

Murex is a recognized global leader in software development for trading, risk management and processing. Every day banks, asset managers, corporations and utilities, across the world, rely on Murex people and Murex solutions to support their capital markets activities. Our motto “pioneering again” sums it all up: since its creation, Murex has reinvented itself time and again to adapt to capital markets revolutions – each time offering innovative software solutions to the industry.

Over 2000 specialists are located across our 17 offices: Beijing, Beirut, Dubai, Dublin, Hong Kong, London, Luxembourg, Moscow, New York, Paris, Sao Paulo, Santiago, Seoul, Singapore, Sydney, Tokyo, and Toronto.

 

Organizing the development of a large software system such as Murex is a challenge. More than 300 developers, among 1000 engineers are working to develop and maintain the 20 millions of lines of code that make up the plateform. At such a scale, identifying costs and opportunities to improve the workflow is an extremely hard challenge. Agile engineering and organizational practices are known to make things better, but it is still difficult to decide when and how much to apply them.

    Goal

    Latest improvements in Data Science like Big Data and Machine learning have proven very valuable tools to predict and optimize how complex systems work. The goal of this internship is to do that with the software development process. In more details, we want to modelize the software development process in order to be able to answer one or many of the following questions :

    • What's the cost of technical debt on feature delivery ?
    • What's the cost of a slow feedback loop on feature delivery ?
    • What's the expected delivery date of a feature based on its position in the feature backlog ?

    Even if it is not possible to answer these questions directly, answers to connex questions would be great.

    On top of that, sharing and explaining the results to non-data-scientists is crucial to the success of the internship.

     

    Means

     

    In order to meet this goal, we'll provide

    • access to plenty of logs and usage data from our internal software engineering tools (version tracking system, defect tracking software, Continuous integration servers, static code analysis systems, automated testing logs)
    • assistance in scripting and data extraction
    • Time to discuss the findings, ideas and to explain our development process