Develop your career with data science

Thinking about a move in your career? Data science has many opportunities

Data Science is all about discovering new insights in data, to make better decisions. Much data is already there: about your company, your processes, your customers, your environment. Why not use this data for better decisions? Data adds another view to your personal views. Data challenges you and makes you sharper. In this article we show you how to do develop yourself and your career with Data Science.

Stay on top of the latest technologies

There are many developments in technologies for Data Science, so staying up to date with the latest techniques is vital if you want to play a key role in data science. The latest Data Science technologies in Machine Learning, Deep Learning, Visualization and Recommender Systems, offer great support in analyzing data to find insights. Above all: machine and deep learning support the use of data and models for both human decision making, e.g. in recommender and decision support tools and in decision making by machines.

Choose the right Data Science methodology

If you want to develop yourself in Data Science it is important to know how to discover, execute and lead a data project. For this you can use methodologies like CRISP-DM. Within CRISP-DM you can start with a dataset to find insights. But it is even better to start and end with decision making, and add business understanding, data understanding, data cleaning and modelling in between.

Get educated

Education can play a vital role in developing yourself in Data Science. Go to a place where they use challenge-based learning for maximum result. And as Data Science should be about creating impact: try to find an educational program where they combine technology with business results. For real impact, Data Science also requires data entrepreneurship; this means being ambitious on your goals, team up, and go outside to benchmark your efforts. Only then you really make business results.

 

How others used Data Science

A Dutch bank, using the CRISP-DM methodology for data science, developed a machine learning model to analyze the total customer portfortfolio on risks and results during the Corona crisis. Based on the results, they developed new approval criteria for loans on sub-sector level instead of sector level. This led to more customers, les risk and more profit. A good data science education program can learn you how to apply machine learning.

Want to know more? Go to Data Science for Professionals

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How others used Data Science

A Dutch group of education specialists used a data project to better analyze and predict the students’ progress. By using the CRISP-DM methodology, Learning Management System data and modelling, they found new performance and prediction insights, which resulted in gains for students and for educators. A good data science education program can learn you how to set up a data project like this.

Want to know more? Go to Data Science for Professionals

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