Why is visualization so important?
How do you determine the goal of visualization?
What is the big difference between explanatory visualization and exploratory visualization?

Who is Florence Nightingale and what is impressive about her?
Why would it be interesting to talk about her at the upcoming PSI conference? She’s famous for her visualization – what could statisticians today learn from her about visualization?

Listen now to learn more!

After a career that brought you as a statistician to various parts of the pharma world, what is the new job, that you just took on about?

What are the unique skills of statisticians - beyond just knowing about stats - compared to many other functions in the pharma world?

Which problems do statisticians need to take care of beyond the current regular work?

How can we make time to tackle these problems?

What skills do statisticians need to improve on to successfully tackle these problems?

Do you effectively communicate complex data?
How can visualization help you when you are
. . . analyzing data?
. . . reporting data?
What initiatives and groups work on this topic and will help you?

Real world evidence (RWE)
Big data
Real world data (RWD)
Pragmatic studies

There are lots of buzzwords floating around and especially with the FDA having a bigger focus on RWE. Many teams in the different pharma organizations concentrate on this type of evidence.

Do you know what your external profile is?
Do you have an idea of how to improve it?

In today's episode, Liz Cole and I will dive deep into a topic called content marketing. It’s kind of meta, since this podcast itself originates on these ideas. Does this sound frightening or disturbing? It shouldn’t.

With so many recent advances in AI, it is important for statisticians to both keep up to date with the most recent methods and getting involved in guiding their application to the most pressing statistical challenges.

In today's episode, Karim and I cover cutting edge examples of how data science and statistical sciences are intersecting. Learn from this episode why different approaches matter when looking at clinical development data.

Do you feel you're working like a firefighter?
Do you have the perception, you're solving the same problems over and over?
Do you worry about ever-changing requests from your business partners?

Then you are not alone - not even alone in the pharma world.

In today's episode, we will talk about the data ops manifesto which addresses such problems. There are actually a couple of such manifestos out there such as the agile manifesto or the dev ops manifesto. These sound similar to Demings 14 principles outlined in his “out of the crisis” publication.

6 effective leadership behaviours for statisticians

One of my favourite leadership podcast run by Olaf Kapinski - unfortunately in German - had a great episode recently (see here for the link to the Leben-Führen podcast: https://leben-fuehren.de/5-wirksame-verhalten-fuer-fuehrungskraefte/?pk_campaign=podcast&pk_kwd=5-wirksame-verhalten-fuer-fuehrungskraefte)

Today, we’re reflecting on the 5 behaviours Olaf mentioned and add a great 6th one, which is very relevant as well.

Can you really do a bigger role?
Did you have a moment in your career, where you were thinking that you as a statistician is put in a box or labelled in such a way that limits your influence?