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Data Science & Analytics

To us, models are an invaluable way in which to enhance and inform the business process. Where a complete and true representation of reality may be impractical or impossible, building and calibrating models is fundamental in approaching observed phenomena in a sound and scientific manner.

Modeling and simulation go hand in hand. While modeling refers to the process of generating a conceptual representation of some phenomenon, simulation captures the practical implementation of a given model — bringing it to life by revealing the dynamic behavioral aspects underpinning the theory. Simulation is particularly useful for stress testing, scenario analysis, or forecasting in those cases, where real-world processes may be represented by models.

Consistent parallel Monte Carlo simulation

At Mirai, we accompany you from the very beginning to the very end: from analyzing and defining the data requirements needed to support your business case, through building the appropriate models and simulation framework, to distilling and critically interpreting the results. We understand that making this successful naturally involves a close collaboration between our professionals, you, and typically several other stakeholders, in order to produce meaningful, acknowledged and decision-relevant insight.
One way of sharing prototypes and bringing people closer together is through Notebooks (e.g. Jupyter, RStudio/rmarkdown). They can help to illustrate the interaction between data and results at an early stage in a transparent and reproducible way.

Our data scientists have extensive experience in data modeling throughout a broad range of applications, with more specific expertise in financial and actuarial modeling, bio-informatics and image processing. We strive to clearly understand the business problem at hand while keeping the bigger picture in mind, and then make use of the technologies which best suit your needs, delivering high-end analytical solutions to your daily business, ready to go.