In the field of statistics, we need specific skills necessary for being successfull. Debarshi Dey, currently the head of the Statistics and Programming and Data Management department at Morphosys, has spent the past 13 years in the pharmaceutical industry. With a PhD in statistics from UC Riverside, Debarshi believes that
We statisticians have always been important for brining new therapies to patients. We design experiments, analyze and interpret data to provide valuable insights that can help make informed decisions. However, the value of our work increases if we’re able to lead others. But becoming an inspirational statistician requires more than
Are you a statistician or data scientist looking to excel in your career and make an impact in the healthcare industry? Today’s episode is inspired by a German podcast that delved into five key reasons for career failure and I fine-tuned this to fit statisticians. As professionals working with complex projects and
If you’re a statistician, data scientist, or programmer looking for quality training opportunities that will help you advance your career, you might want to look into The Effective Statistician Academy. This exclusive academy offers a range of courses that cover essential topics in the field of statistics. From leadership to
What strategies do you use in your work as a statistician to ensure successful outcomes? How do you set expectations with stakeholders when tackling a project?Are there any common mistakes statisticians make when setting expectations in their job that you have learned to avoid?How setting realistic expectations can positively impact
What knowledge gaps exist regarding the implementation of these new analytical techniques, and how can statisticians and data scientists bridge them to maximize effectiveness of clinical research? Despite the promises of Bayesian approaches, the lack of expert training, software tools, and computational resources has made their adoption slow. Statisticians and
As statisticians, we rely on good quality from programmers and data management. And if you talk to your colleagues, everybody has a story about a poor experience. But the questions are: How do we collaborate with other departments to create a quality deliverables?How to strike the right balance between working
For years, creating data visualizations has frustrated statisticians, data analysts and data scientists. Software – especially SAS – hasn’t been great and organisation have tried to take the pain out of the process by creating standard figures. But these standard graphics fail to communicate the message to the intended audience
Have you been considering a one-armed observational study or asked to work on such a study? As a statistician, it is important to understand the scientific but even more the political background of such studies. In this episode, we will discuss one-armed observational studies and why they are, in most
The world of healthcare continues to change, and it’s important to keep up with the latest advances in technology and research. That’s why I’m excited to talk with Shirley Wang, one of the leaders of RCT Duplicate, a study focused on duplicating randomized clinical trials through real world data. She is currently leading
Today I’m talking with Rachel Tham, a principal statistician, about a book that has been incredibly impactful in both of our lives—Deep Work. We discuss what deep work is and how it can help statisticians at work. Deep work is a concept developed by Cal Newport which encourages people to
Why are companies often running single arm studies in development? What are the potential drawbacks and why is it not a binary choice between full comparative study and single arm trial? What are solutions in between to find a balance between feasibility and rigour? Single arm studies are a popular
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