

The Effective Statistician - in association with PSI
Alexander Schacht and Benjamin Piske, biometricians, statisticians and leaders in the pharma industry
The podcast from statisticians for statisticians to have a bigger impact at work. This podcast is set up in association with PSI - Promoting Statistical Insight. This podcast helps you to grow your leadership skills, learn about ongoing discussions in the scientific community, build you knowledge about the health sector and be more efficient at work. This podcast helps statisticians at all levels with and without management experience. It is targeted towards the health, but lots of topics will be important for the wider data scientists community.
Episodes
Mentioned books

Mar 30, 2020 • 19min
Learnings from the COVID crisis for statisticians
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I discuss my learnings, my reflection about this, and what is the meaning of this situation for us, statisticians, and more significant factors like the following:
Hardly any tables out there, but lots of visualizations both interactive and explanatory - still most of our day-to-day jobs are providing tablesTables are not the key deliverables episodeInterview with Zak Skrivanek - a figure says more than 1000 tablesWonderful Wednesday episodeVIS SIG Get the data from many different sources - not just the one source at hand: e.g. the study currently working on; RWE, literature data, and other studiesMany misunderstandings on the sources of the data and comparisons across different sources (e.g. different countries) and then infer on the differences between the policy making in the different countries - where are the statisticians in the news explaining the numbers?We need more leadershipOur associations need to step up and become more professional and impactfulWe have a responsibility hereResponsibility for providing the numbers but also gives the background and advise on how to use the numbers - for example John HopkinsFAQ not really helpfulWhat can be answered here and what notHow reliable is the data?What are the strength and limitations?Any guidance on the use of the data?Do we train people on how to read our data? Or do we just through the tables over the fence for someone else to deal with it?Power of scenario simulations - Washington Post article - great to show conditional probabilities e.g. if you have different prior information in Bayesian analyses
Listen to this timely episode and let me know what you think!

Mar 23, 2020 • 36min
Working from home - is this for you?
Interview with Jürgen Hummel
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In this episode, Jürgen and I discuss about the following points:
Why is working from home beneficial for the statistician and the employerWhat tasks are especially suitable for working from homeWhat tips do we have to make working from home successfulHow to balance office time and home office time
Learn more by listening to this episode and share this link with others who might be interested in working at home!

Mar 16, 2020 • 33min
Data visualization - the often overlooked basics
Episode 1
In today's episode, I review the different things you need to consider in creating an effective data visualization when presenting, which is the following:
Who is the audience?Level of understandingKOLResearcherStatisticiansWhat is the medium?PresentationEmailPaperHow much time do you have?Who is the presenter? Is there one at all?Understand how your visualization is used downstream
References:Storytelling with data - cole nussbaumer knaflicTamara Munzners book Visualization, Analysis and DesignDatastori.esBig book of dashboardsMakeover MondayD3 gallery on githubSpecial interest group VISData visualization society
Listen to this episode to learn from it, and share it with others!

Mar 9, 2020 • 42min
Learnings from Florence Nightingale
Interview with Deborah Ashby
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Despite her having a weak position in society at the time - being a nurse and a women – she still was very influential and achieved a lot. Many statisticians feel like they are not part of key decisions and don’t have the impact, they could have. What can we learn from her in this regard?
References:Link to the homepage of the conference keynote speakers
Link to the home page of the conference
Listen to this episode and learn more!

Mar 2, 2020 • 53min
Problems for statisticians to take on
Interview with Stephen Pyke
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In today's episode, Stephen and I discuss the PSI strategy day in 2019 and focused on the following points:
My own journey - statistics and beyondHoliday reading - people respond to incentivesClinical development - Our main job: minimize value destructionAddressing the challenges of low productivityProblem that needs more attentionTime - Study enrollment time is often an important source of uncertainty in project plansQuality - Detecting site quality issues quickly is criticalCost - Trial costs are more likely to increase than reduceStatistics at the interface - Partnering with other disciplines
Listen and learn from this episode now!

Feb 24, 2020 • 39min
Wonderful Wednesdays
Interview with Rachel Phillips and Mark Baillie
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n today's episode, we talk about the advantages of using visualizations when analyzing and communicating data. We also discuss the following points:
In today's episode, we talk about the advantages of using visualizations when analyzing and communicating data. We also discuss the following points:
How our organizations prioritize visualizations?What we love about visualizations?What are the principles of visualization statisticians should know about?How to create interesting, innovative, and purposeful visualizations?
Listen to this episode to learn more on visualizations and share this with others who might learn from it!
References:
Visualization special interest group (VIS SIG)Wonderful Wednesday announcement and link to registrationGoogle team BigPictureGoogle tutorialDatastori.es episode on visualization of uncertaintyGithub D3 galleryNovartis visualization initiative and cheat-sheetStratos initiativedata visualization societyFundamentals of Data Visualization - online bookData Visualization - A practical introduction - online book

Feb 17, 2020 • 1h 29min
RWE demystified
Imi Dean, a real-world data scientist at Roche with expertise in oncology and machine learning, shares insights on the impact of real-world evidence in healthcare. He discusses his journey from medical science to data science, highlighting the power of real-world data and its contrast to traditional trials. The importance of precise research questions and overcoming biases in data is emphasized, as well as the role of propensity scoring in treatment analysis. Ultimately, Imi reveals how real-world evidence can significantly enhance patient care and decision-making.

Feb 10, 2020 • 47min
How and why to increase your external profile!
Interview with Liz Cole
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Listen to our conversation and understand:
What is content marketing?Why is this relevant for statisticians working in CROs, pharma or as consultants? How can content help CROs or consultants win more business? How can content help you attract candidates to your team and stand out as an employer?How can content help to boost your personal profile? What are the barriers that stop people from implementing content marketing and how we overcome these barriers? What actions do you recommend should statisticians start with?What resources do you recommend helping with content creation and content marketing?
Listen to this episode and learn from it!

Feb 3, 2020 • 44min
Impact of AI on Clinical Development
Interview with Karim Malki
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Karim shares about his career, his roles, and different approaches and methods. We also discuss the following points:
Machine learningAIPredictive analyticsData scienceDifferent statistical methods and limitationsDifferent tools and applications Statistical innovation
Listen to this episode, learn from it, and share it with others!

Jan 27, 2020 • 1h 2min
The data ops manifesto
Interview with Christopher Bergh
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The data ops manifesto can be found here and lists these 18 points - some of which are discussed in more detail in this episode.
Data Ops Principles:
Continually satisfy your customerValue working analyticsEmbrace changeIt's a team sportDaily interactionsSelf-organizeReduce heroismReflectAnalytics is codeOrchestrateMake it reproducibleDisposable environmentsSimplicityAnalytics is manufacturingQuality is paramountMonitor quality and performanceReuseImprove cycle times