Hereby, in unknown regions of the conformational space, new electronic structure calcula-tions are performed and the results are added to a database. In regions, where calculations have already been performed, the fitting algorithm is used to interpolate the stored data and no further electronic structure calculations are needed, as implemented for the directdynamics variational multi-configuration Gaussian (dd-vMCG) approach in the Quantics program package. In recent years, computational statistical learning methods (machine learning, neural networks, deep learning, unsupervised clustering, etc.) have found to provide very promising approaches to construct PE surfaces of high dimensional systems. Using those fitted potentials, the computational time for molecular dynamics simulations can be substantially reduced. This was successfully shown for both, ground-state molecular dynamics simulations and (nonadiabatic) excited-state simulations. In this work, we introduce PySurf, a new software framework for data-science applications in computational chemistry. The software package is specifically designed for rapid development and prototyping of new algorithms using the Python programming language at its core. The code comes with a powerful Plugin engine, which allows straightforward extensions of the existing functionality with custom modules, that naturally fit into the existing environment. Its Workflow engine enables very fast development of customized work and analysis schemes. An implementation of nonadiabatic surface-hopping using the Landau-Zener scheme 32 is presented. The methodology was applied to a pyrazine model system and to investigate the S 2 /S 1 conical intersection of SO 2 , based on ab-initio calculations.