Time: 15:00 - 16:30 UK Time Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
About the Presenter
Research Fellow, Advanced Analytics at Eli Lilly and Company
Richard Pugh
Abstract
Looking over the fence: What does Data Science mean outside of life sciences and what can we learn? The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
Time: 15:00 - 16:30 UK Time Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
About the Presenter
Research Fellow, Advanced Analytics at Eli Lilly and Company
Richard Pugh
Abstract
Looking over the fence: What does Data Science mean outside of life sciences and what can we learn? The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
Time: 15:00 - 16:30 UK Time Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
About the Presenter
Research Fellow, Advanced Analytics at Eli Lilly and Company
Richard Pugh
Abstract
Looking over the fence: What does Data Science mean outside of life sciences and what can we learn? The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
Time: 15:00 - 16:30 UK Time Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
About the Presenter
Research Fellow, Advanced Analytics at Eli Lilly and Company
Richard Pugh
Abstract
Looking over the fence: What does Data Science mean outside of life sciences and what can we learn? The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
Time: 15:00 - 16:30 UK Time Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
About the Presenter
Research Fellow, Advanced Analytics at Eli Lilly and Company
Richard Pugh
Abstract
Looking over the fence: What does Data Science mean outside of life sciences and what can we learn? The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
Time: 15:00 - 16:30 UK Time Presenters: Dr Joachim Schwarz, PhD Todd Sanger and Richard Pugh
Presentations:
1. 'Looking over the Fence' by Richard Pugh - Click here to view the slides
2. 'The Use of Predictive Modelling in Customer Relationship Management' by Joachim Schwarz - Click here to view the slides
3. 'Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly' by Todd Sanger - Click here to view the slides
Dr Joachim Schwarz
Abstract Predictive Modelling in the field of Customer Relationship Management
The webinar focusses on one main problem of every customer relationship management department: How to identify those customers, which are more likely to e.g. terminate their customer relationship or to buy a new product? One way to solve this is predictive modelling. We will have a look on typical data a company has about their customers, and how it can be used to develop a model to predict a specific customer behaviour. A special focus will be laid on limitations of this approach and, last but not least, its specific potential to generate or to save money.
About the Presenter
Dr Joachim Schwarz, studied mathematics at the Georg August University in Göttingen and at Trinity College in Dublin. He did his PhD in business administration at the private university of Witten / Herdecke, and afterwards, he has more than nine years working experience as manager and team leader in the analytical CRM department of the Deutsche Telekom, with special focus on data mining and predictive modelling. Since winter term 2013, he is professor for business mathematics and statistics at the FOM university of applied sciences in Bonn.
PhD Todd Sanger
Abstract
Moving from R&D to Sales and Marketing: the business analytics experience of a statistician at Lilly Typically, pharmaceutical companies invest more money on sales and marketing than they do on R&D, yet very few statisticians work to support sales and marketing organizations. At Lilly, we created a group of statisticians to support analytical problems in Sales and Marketing. This talk will describe the types of issues we encounter and the statistical techniques we use to tackle these issues.
About the Presenter
Research Fellow, Advanced Analytics at Eli Lilly and Company
Richard Pugh
Abstract
Looking over the fence: What does Data Science mean outside of life sciences and what can we learn? The last 10 years have seen significant growth in companies investing in Big Data, Data Science, Machine Learning and AI. The key driver for organisations investing in these initiatives is to generate insight from data that can be used to drive better decision making. However, as each industry has different aims and constraints, the adoption of data-driven approaches can vary significantly.
This presentation will look at core concepts of data science, such as the 3 Vs of data, and how different industries have looked to implement these concepts. In particular, we will look at possible opportunities for the pharmaceutical sector to adapt successful approaches from other industries.
About the Presenter
Richard Pugh is Chief Data Scientist and co-Founder of Mango Solutions, a Data Science consulting company specialised in the pharmaceutical industry. Richard studied Mathematics and Statistics at the University of Bath before working as a biostatistician within the life sciences industry. Richard then joined Insightful, working as a Consultant across many industries around the application of statistical methods using the S-PLUS software product. In 2002, Richard co-founded Mango Solutions to focus on the application of analytics to solve business challenges using technologies such as SAS, S-PLUS and R. Richard is heavily involved in the R community, co-authoring the book “R in 24 Hours”, and was the first President of the R Consortium. Richard is an active member of the committee of the RSS Data Science Section. Today, Richard spends much of his time advising clients across a variety of industries on data-driven approaches, and is a regular speaker at analytic conferences.
PSI Introduction to Industry Training (ITIT) Course - 2026/2027
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry. This month’s session, “Graphics Basics,” will introduce the fundamentals of producing graphics using the ggplot2 package.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
PSI Book Club: The AI Con – Joint with ASA Book Club
The Guardian described the authors of this book as refreshingly sarcastic! What is sold to us as AI, they announce, is just "a bill of goods": "A few major well-placed players are poised to accumulate significant wealth by extracting value from other people's creative work, personal data, or labour, and replacing quality services with artificial facsimiles."
PSI Book Club: Another Door Opens – Book Club Special Event
This is a Book Club Special Event in response to the changes in our industry and as a supportive move to create community and connection for those navigating redundancy and uncertainty. Read the book in advance of the book club session then join the zoom call to discuss ideas. There will be breakout groups to connect with others, exchange experiences of how the book has helped, and offer support.
PSI Book Club: Change: How organisations achieve hard-to-image results in uncertain and volatile times
Organizations have to adapt to the transforming landscape of our industry to ensure they continue to be successful in the future. Many of us are feeling the impact of organizational change. By reading John P Kotter’s book we can understand about organizational change and learn how to thrive, rather than just survive, through change.
Change, by John P Kotter (and his team), is a summary of all that he has learned over his decades of research and leading change. His book describes why many current approaches to change are inadequate and explains why new solutions need to give people a voice and a role in a new, change-embracing organization.
Develop your understanding of organisational change and become empowered to be part of your organisation’s change, by reading Change by John P Kotter and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply knowledge from the book in-between sessions.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
A Lead Statistician builds and leads teams of statisticians and representatives from other functions and ensures the use of appropriate and efficient statistical analysis methods during development of Bayer products
As a Statistical Programmer II at ICON, you will play a vital role in the development, validation, and execution of statistical programs to support clinical trial analysis and reporting.
Leeds Clinical Trials Research Unit - Undergraduate Internships
The Internship is open to undergraduate students in the penultimate year of their undergraduate degree at a UK university, in a mathematical, statistical, or quantitative related field.
: We have an exciting opportunity for an Associate Director (AD), Statistical Programming, to join a passionate team within Advanced Quantitative Sciences- Development.
Novartis - Senior Principal Statistical Programmer
We have an exciting opportunity for a Senior Principal Statistical Programmer, to join a passionate team within Advanced Quantitative Sciences – Development.
Pierre Fabre - Clinical Development Safety Statistics Expert M/F
We are seeking a highly skilled and proactive Clinical Development Safety Statistics Expert to join our Biometry Department and the Biometry Leadership Team based in Toulouse (31, Oncopole) or Boulogne (92).
Pierre Fabre - Lead Statistician – Real World Evidence -CDI- M/F
Pierre Fabre Laboratories are hiring a highly skilled and experienced Lead Statistician – Real World Evidence (RWE) to join the Biometry Department, part of the Data Science & Biometry Department, based in Toulouse (Oncopôle) or Boulogne.
Pierre Fabre - Lead Statistician- Clinical Trials M/F
We are seeking a highly skilled and experienced Lead Statistician in Clinical Trials to join our Biometry Department based in Toulouse (31, Oncopole) or Boulogne (92).
Veramed - Manager/Senior Manager Statistics for Consultancy Team
An opportunity has arisen for a Statistician to join Veramed’s Statistical Consultancy Business Unit full time. The opportunity will be to provide statistical support to a variety of clients.
As a Senior Statistician, you will provide high-quality statistical support to one of our key-FSP clients. At Senior level you may also take on a supervisory role (e.g. line management and/or project management), depending on your experience and interest.
As a Senior Statistician at Viatris, you will take a leading role in designing clinical studies, guiding statistical strategy, and ensuring that statistical deliverables meet the highest scientific and regulatory standards.