Data Science

Turn (big) data into practical insights, valuable models, and automated systems.

Analytics with an edge?

Advanced Analytics

The Advanced Analytics expert will take matters further where the Data Analyst cannot. An in-depth analysis that can transform your organisation requires advanced technical skills and knowledge of modelling methods. What are the secret controls that need to be turned? How many people should a new user of a social media platform follow to have virtually guaranteed long-term activity? Our people can help you.

Are the data and skills available but can you still achieve more?

Analytics Translator

Data is on the rise and organisations are improving their data teams and infrastructures, yet often something is still missing: the translation between the data people and the rest of the organisation. Not only do solutions need to work technically, but they also need to be understood and used by the end user. Our Analytics Translators provide this link. They ensure that the Data Analyst can collaborate with the IT department as well as the Customer Service Officer in the interest of the organisation as a whole.

Leading the way with operational Data Science models?

End-to-End Data Science

Our industry-leading experts design and implement AI solutions that deliver measurable value. We are keen to share our effective principles with our partners around the world. Modern and results-oriented solutions start with the right business question and the right data. Then you build an appropriate model and apply it. Our Data Scientists develop and operationalise technical and non-technical frameworks. Our solutions are usable, small and light, flexible and built-to-change.

Want to know more?

Joachim would gladly introduce you to our Data Scientists.

Joachim van Biemen

Business Manager+31(0)20 308 43 90 +31(0)6 23 59 83 71 joachim.vanbiemen@digital-power.com

Our Data Scientists have worked on:

The COVID-19 Violence Tracker

The outbreak of the corona pandemic in early 2020 has turned the world upside down. In addition to countless infections, hospitalisations and deaths, we also saw an outbreak of violence in many countries. Citizens took to the streets, sometimes violently, to protest against the measures taken, but domestic violence also increased in many places and fear and frustration played a role in racism.

Reliable insight into crowds on trains and stations using an algorithm

An increasing number of people are traveling by public transportation. Several stations in The Netherlands are being rebuilt or renovated to keep up with the growing number of train passengers. For the rebuilding and layout plans, information was needed on station traffic. NS Stations also wanted to improve transfer safety in collaboration with ProRail.

Determining the location of gardens using Data Science

Residential investor Vesteda is working on a new website. If an available rental home has a garden, the location of the garden must be listed on the webpage of that home. This information was not yet available in the database. We were instructed to determine the location of the garden based on the coordinates of the homes.

How text analysis helps RNW Media to listen and take action

RNW Media builds online communities in countries with limited freedoms. In these communities, young people can read and discuss sexual and reproductive health and rights (SRHR) and civil rights. In addition, RNW Media is working on advocacy – putting the interests of young people on the map with governments.

Application of Natural Language Processing (NLP) and text mining for process improvement.

Fair Wear is a non-profit organisation that aims to improve the working conditions of employees in garment factories. The NGO has collected a lot of documentation about its activities in recent years, for example in the form of reports from a complaint line for factory employees, reports of audits that check whether factories comply with the guidelines, and reports of training for factory employees. This information is stored as typed text, usually in Word or PDF format.

Social listening in the real estate market

Vesteda was curious if social listening – monitoring and analysing social media discussions about a brand, competitors, products or hashtags/keywords – could add value to the organisation. To this end, we started a project that consisted of two parts: exploring possibilities for social listening in the Corporate Communication department and applying social listening in an ongoing Data Science project.

Join our team as a Data Scientist?

Currently, we are not searching for Data Scientists, but we do want to expland our Data Engineering team. Curious about this role?

View the vacancy

We fully understand that several employers are promising you a dream job. This is why we list what makes Digital Power unique.

Best of both worlds - a down-to-earth group with the most challenging assignments
Room for initiative: you shape your own career
Cool clients in different sectors (both profit and non-profit)
Unique team with unique synergy: we are proud of each other, give each other everything and have no in-house competition or unnecessary hierarchy
Entrepreneurship is encouraged: do you see a great opportunity for us? Go get it!
Creative and out-of-the-box mentality: 'I've never done it before, so I think I can do it'
Strong emphasis on learning and development through our internal Data Academy, unlimited training budget and hugely motivated colleagues
Humour, fun and a family feel: be yourself!
Lots of table football games
A great work-life balance
Friday afternoon gathering for which many come to the office especially
A team outing every quarter

Are you thinking: this might be where I will feel at home? Check out our vacancies and apply now!

As a consultant in our team, you must be able to collect, analyse and visualise large amounts of data. You then translate the insights you get from the data into concrete actions for different stakeholders.

Therefore, you must be able to relate well to your client's organisation: a Manager wants to see different information than a Data Analyst or Developer. As a consultant, it is therefore important that you speak different 'languages'.

During your assignment, you will constantly delve deeper into the organisation, actively ask questions and listen carefully to the client. This is how you find out what the real issue is and who you need to work with to get the most out of your assignment.

The type of assignments you carry out depends on your job profile, the customer demand and your personal requirements. Sometimes you will have one 40-hour assignment per week, but you may also divide your time between several, different assignments at the same time.

Most assignments take place at the client's location. Sometimes, you may work with colleagues from our office on an assignment (e.g. a dashboard for a client). It is also possible to collaborate on in-house projects.

Below are examples of assignments in the field of:

Technical Web Analytics
Data Analytics
Customer Experience
Data Science
Data Engineering

The full overview can be found here >

Be inspired about Data Science

How does Data Science work in daily practice?

Organisations wanting to get started with data quickly ask for Data Science solutions. Data Science is often seen as the holy grail of data-driven working. But what does a successful Data Science project actually look like in practice? And how can it serve your organisation? In this series of articles, we take you through all the elements you need to achieve success for your organisation with Data Science.

How do you find the right data scientist?

More and more organisations are getting started with data science. A logical consequence of this is clearly a growing number of related vacancies. But how do you set up a useful job description for a data scientist – and mostly: how do you actually pick the right one? We're giving you some hints on what to do, and what not.

Why do I need Data Engineers when I have Data Scientists?

It is now clear to most companies: data-driven decisions by Data Science add concrete value to business operations. Whether your goal is to build better marketing campaigns, perform preventive maintenance on your machines or fight fraud more effectively, there are applications for Data Science in every industry.

What is Data Science?

Everywhere at events and online, stories are told about what 'data science' is all about. Definitions are anything but consistent. They go from 'getting something of value out of data' to 'it's basically the same as statistics'. And a Data Scientist is 'a data analyst who lives in Silicon Valley' or 'a socially skilled IT person who does something with data'. But what is it really?

What is the data pressure cooker?

Consultancy.nl interviewed our Alex about the data pressure cooker. We launched this new service in spring 2020. During a data pressure cooker, we spend 5 days working with an organisation's data. Based on the outcomes, the client decides whether it wants to take further steps in the field of data-driven working.

Social Network Analysis: how to gain insight into social media networks

If your organisation is active on social media and you want to optimise the online strategy, you need to know what is happening online around you and the impact of your activities. Social Network Analysis can help you with that. We explain what it is, how it works and the purposes it serves.

How to use Social Network Analysis to understand public opinion

The Corona measures are a much discussed topic on Twitter. The crisis team not only fights against Corona's effects on public health, but also tries to maintain legitimacy for the decision to keep certain measures in place among the public. With this practical case we explain how you can make public opinion on Twitter transparent with Social Network Analysis.

From ethical data to action

The introduction of the new privacy law (GDPR) in 2018 has ensured that many organisations put privacy high on the agenda. In this article you can read about the 5 ethical risks of working digitally and using data. We also share a concrete solution: the Responsible Data Framework.