Developing the Next Generation of Skills for Statistical Programmers

Posted by Cytel

Apr 18, 2018 6:09:00 AM

Our recent Clinical Biometrics Survey explored the views of respondents from across the statistical programming, biostatistics, and data management functions to learn their top challenges, and most important perceived industry trends and skills development. In this blog, our Ajay Sathe gives his perspectives on the key areas of personal and knowledge development that he believes statistical programmers need to focus on to keep abreast of the evolving drug development landscape. 

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Always develop new skills (and visualization is high on the list)
The output that we create as statistical programmers is continuing to evolve – becoming much more alive and dynamic, in contrast with the static standard tables and listings that we used to create a decade ago. Nowadays, the outputs that we produce are increasingly delivered on electronic devices, in formats that allow the end user to interact with them in multiple ways.
The forward-thinking statistical programmer needs to constantly reinvent herself or himself to be able to generate this type of output. To achieve this, we need to engage in a continual process of learning and skills development. It’s not enough to be only a SAS programmer anymore, we need to acquire diverse and modern skills. One of the tools that ranks highly is R-programming, among other rising stars such as Python, text analytics, big data technologies and so on.


Get to grips with the therapeutic areas you work in
Traditionally, programmers tended to be experts only in programming, and did not think much about immersing themselves in the pharmaceutical domain. That's not enough in the current environment. Statistical programmers need to understand much more about the therapeutic area in which they are working. Oncology is a particularly complex area with a great deal of clinical trials activity. Therapy areas like multiple sclerosis, endocrinology, diabetes also have an evolving therapeutic landscape with complex and sophisticated methods. It’s very important for the statistical programmer to understand how new therapies work, and how they're developed, to be able to do the most effective job.

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Learn to deal with messy data
Traditionally, statistical programmers used to work with very clean, well-structured and disciplined data. Increasingly, we are dealing with data coming from diverse sources, such as text from social media, for example. Statistical programmers need to acquire techniques that can help them make sense out of those data and extract and apply the relevant information. In areas such as real-world evidence, which is becoming increasingly important, such techniques are extremely important.


Be a generalist to become a better specialist
The most important piece of advice I give to our CliPLab students is that they need to become generalists, and not focus their knowledge development only on programming. It’s important to gain a foundation of understanding in related disciplines like statistics, data management, and pharmacology. Paying attention to all of those will serve as a solid grounding for expertise in programming.

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Listen and question to communicate better
In today's context of global collaboration, one of the absolutely critical skills for success is communication. Technical people sometimes play down the importance of communication, believing that extraordinary programming aptitude alone will make for a good career. In fact, communication – in terms of expressing yourself clearly and unambiguously– often becomes more important than technical prowess. There are three attributes to communication which really matter: clarity, brevity, and precision. These are especially important when collaborating in a global team. Of course, communication doesn't only mean speaking, it also means listening and to be able to glean the important pieces of what you heard, as well as reading between the lines. The final factor of good communication is the ability to ask the right kind of questions. With our CliPLab trainees, and within Cytel itself we make a concerted effort to train people on how to ask the right kind of questions.

Want insights on what statistical programmers see as the biggest challenges, trends and skills development needs in the sector?  Click the button below to download our Clinical Biometrics Survey report.

ReportCytel statistical programmers do meaningful work in a collaborative and innovative environment. To learn more about our careers, click the button below.  Attending PharmaSUG 2018 in Seattle?  Meet our talent experts at Booth #7 to discuss careers opportunities.

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Cytel's recent webinar on CDISC programming reflects our most recent thinking on statistical programming. Click below to play. 

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About Ajay Sathe

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Ajay Sathe is Chief Executive Officer of Cytel's India Operations, headquartered in Pune, India. Ajay oversees the delivery of software development and biometrics outsourcing services within the region. His strong management track record includes applications development, product management and governance of outsourced services.

Prior to joining Cytel Inc., Ajay was Founder and Technical Director at Spectrum Business Support Ltd., where he led teams building both WordMiner, an information retrieval library, and Jurix, a law information service.

Ajay Sathe studied Electronics Engineering at Banaras Hindu University, India, and received his MBA from The Indian Institute of Management, Ahmedabad.

                                                                                                                         

Topics: Statistical Programming, SAS, R language, clinical data management, biostatistics

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