Why work together with Aurai?

Aurai is a young company with a concrete vision and a constant drive to improve and innovate. I love that. Aurai has distinguished itself from most other companies I have worked with by its can-do and common sense attitude and culture. I find it fun and challenging to introduce a group of junior data scientists, most with little professional experience, into the world of Design Thinking. One of the most interesting parts is training them in communicating with the internal and external clients to craft end products that are more relevant and impactful. Design Thinking is a great example of a no-nonsense attitude. During the workshops and training I can do what I like best: combining my academic background and professional expertise with helping people while gaining experience in new knowledge and tools.

What does Design Thinking training look like?

We run a mini Design Sprint in the introductory training at Aurai. We do this by presenting the trainees with a real case. I guide the new trainees through the first steps of the Design Sprint process for two days until the plans for the prototypes are ready. After that, the group begins creating the prototypes with real data. In the following months, I periodically meet with them to provide them more depth on Design Thinking. At this stage we dive deeper into the practical tools and key mindsets.

What is the added value of Design Thinking?

Conceptually, Design Thinking is used for understanding and solving problems; we define a problem, come up with ideas to solve it through the simplest solutions and then present the finished product to future users. Researching and analyzing both internal and external problems and their solutions for customers can range across various operations. One of the most helpful insights data scientists utilize to increase the impact of the design and data for organizations and customers is understanding why and how future users will use a new tool or information. Another important element of Design Thinking is to approach the work in small steps. This ultimately increases both the impact and speed of a project as we work to complete it with colleagues from other organizations.

Interested in our Data Science traineeship? Sign up here!