Hillenraad Data Refinery, a data science consultancy active in the horticulture industry, is a collaboration between Hillenraad Partners and Data Refinery Amsterdam.With this partnership, expert knowledge of the horticulture industry is combined with deep knowledge of data science and its application to a wide range of organisations. Together we focus on empowering organisations to help them to become more data driven.

1 day a week training on Data Science skills by Sr Data Scientists of BigData Republic. Trainings include:- Data science essentialspython, linux, virtual boxes, programming and scripting skills- Modellingdata analysis and visualisation, statistics, classification & regression- Specific applicationsprocess mining, network search - Improved modellingunsupervised modelling, classification & regression techniques- Advanced modellingbayesian/statistical modelling, advanced classification techniques, time series, deep learning. - Soft skillsconsultancy skills, time management, getting things donewww.dpadatascience.nl

The main task is to construct the SMA (Standardized Measurement Approach) implementation by developing a re-positioning of the Operational Risk internal model (AMA – Advanced Measurement Approach) and Scenario Analysis. Thereby, the job entails supporting in the quarterly capital calculation (fitting deviation process), the EU-wide stress test, validation of scenarios and Credibility Weights and reviewing the follow-ups on ECB-MVB-CAS findings.

During this fulltime internship at the Actuarial Services of EY, a stochastic partner model is developed that can estimate and forecast the partner frequencies. Currently insurers and/or pension funds use partner frequencies for the individual value transfers. These frequencies are based on outdated industry-wide research results that are constant since 1995. The model constructed in this research takes a time trend and different age effects into account leading to more accurate partner frequencies. These more accurate partner frequencies lead to outstanding cost savings for the insurer.

During this fulltime internship at the Financial Department of the Erasmus MC, 4 models have been developed with the available data in the Financial Data Warehouse to provide insight in the intensity of care. In addition, several recommendations have been provided to optimise the data and to enable a better estimate of the intensity of care.