Financial advisory and quantitative modeling for banking and fintech
Lunalogic is a Paris-based financial consulting firm built on a polyglot stack (Java, Python, C++, Scala) designed for quantitative risk and pricing work. The tech foundation—Kafka, Hadoop, Spark, Azure Kubernetes—points to heavy lifting in distributed computing and real-time event streaming, matching their active projects in risk calculation services and stress-test simulation. Engineering hires at mid and senior levels signal ongoing platform scaling to support high-volume, low-latency financial models.
Lunalogic advises financial institutions—traditional banks, asset managers, fintech companies, and insurers—on quantitative strategy, risk management, and digital transformation. Established in 2000 and independent, the firm operates across pricing models for interest-rate derivatives, stress-test frameworks, and cross-asset portfolio systems. Current technical focus includes distributed risk-calculation services, event-driven architecture, and moving models from research into production infrastructure on Azure.
Java, Python, C++, and Scala are core languages in the stack, supplemented by C#/.NET and Visual Basic. This mix reflects quantitative modeling (Python, Scala) and high-performance systems work (Java, C++).
Yes. 4 of 5 active roles are engineering positions (mid, senior, and lead levels) posted in France and Canada, with hiring velocity accelerating.
Azure is the primary cloud, with Kubernetes, Azure Event Hubs, and Azure Service Bus for distributed services and event streaming at scale.
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