MSJ - Modelling & Statistics for You

I am passionate about science, modelling, and statistics. For the past 10 years, I have engaged in hands-on mathematical modelling myself, trained others, and built and led teams. During that time, I have learned that companies are most successful if they focus on the following four pillars: data-driven decision making, mathematical resilience, demystifying data science, and dedicated symbiosis. To support any or all of the four pillars, I have divided my services into hands-on modelling, training, and consulting.

Owner

Provincie Zuid-Holland

Consultant on the use of mathematical models for policy. Aim is the development of a low-level guidance for a proper evaluation of models, and if/how to implement them.

Consultant / Researcher

Ferring Pharmaceuticals

Using a RWE dataset on the effectiveness of a lifestyle intervention app to:
1. create a statistical analysis plan (SAP). 
2. apply the SAP for statistical analysis. 
3. Use the design, analysis and results of the study for manuscript writing and publishing.

Statistical Consultant

Stichting De Menselijke Maat

Academisch onderzoek naar een mogelijke relatie tussen vaccinatie en oversterfte

Onderzoeker

Unica

Development and deployment of machine learning models for refrigeration technology using Azure ML.

AI Consultant & Machine Learning Engineer

Yookr

Hands-on modelling, training and consultancy towards the development of an AI-system to enable digital services for greenhouse horticulture, open cultivation, public space and sport fields

Statistical Consultant & Machine Learning Engineer

Innosens

- Network meta-analysis
- Coset-Effectiveness modelling
- Budget Impact modelling
- Real-world evidence design & analysis

Modeler - Health Economics and Outcomes Research

Lexsigma Healthcare

Verity Barrington

Specialist AI expert

Uitgeverij Walburg Pers

Using a model without wisdom always leads to accidents, as we explained in our previous book. Using AI without wisdom has the same consequence, only in this case the potential consequences are extreme because of the scale at which these models are used and exploited. We offer a reflection on these developments, with technical and philosophical components.

Author: The demystification of AI. A plea for the use of common sense.

What do the Dutch benefits affair (Toeslagenaffaire), the damage caused by earthquakes in Groningen, the corona pandemic, the nitrogen dossier, the financial crisis and the climate dossier have in common? All these dossiers have been or are being studied with models, and many decisions have been taken based on those models. It is important that there is more social awareness about models, and this is where our book 'From earthquake to zoonosis' comes in. After reading, everyone should be able to understand what models do and don't tell, and how to use them wisely. Models can help, but only as the beginning of a conversation and not as the end point. In an accessible and philosophical way and based on the major social themes of our time, we discuss how mathematical models can and cannot be used.

Author: From earthquake to zoonosis: on using models for policy

I am passionate about science, modelling, and statistics. For the past 10 years, I have engaged in hands-on mathematical modelling myself, trained others, and built and led teams. During that time, I have learned that companies are most successful if they focus on the following four pillars: data-driven decision making, mathematical resilience, demystifying data science, and dedicated symbiosis. To support any or all of the four pillars, I have divided my services into hands-on modelling, training, and consulting. (https://msj-advies.nl/)

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Dr. Marc Jacobs

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