In this latest edition of our Career Perspectives series, we had the privilege of interviewing Guillaume Hervé, Director Statistical Programming in PBS. Guillaume shares his journey in statistical programming, highlighting his extensive experience and pivotal roles. He discusses Cytel’s collaborative culture, innovative project management approaches, and the importance of mentorship. Additionally, Guillaume offers insights into the skills essential for success in the field and advice for aspiring statistical programmers.

Can you give us a little background on your career and your professional journey so far?

After completing my master’s degree in biostatistics and multiple internships as a biostatistician, I started my career as a statistical programmer 14 years ago at Novartis in Rueil-Malmaison (near Paris). I was quickly promoted to lead programmer, a position that allowed me to express my full potential as both a programmer and a team lead. During those 8 years, I gained a solid foundation of knowledge and experience in the pharmaceutical industry, especially within biometrics and clinical trial management.

In 2018, Cytel opened their new office in Basel, which is where my journey with Cytel began. I now had the opportunity to evolve in a new environment — the world of CROs. Cytel was expanding, which opened the door for me to consolidate and strengthen my experience as a team leader and provided me with the opportunity to take on the role of operational manager, and later line manager. I currently supervise a team of 20+ programmers across various regions, including Europe and APAC.

What is your role at Cytel?

I’m Director of Statistical Programming for Cytel’s Project-Based Analytical Solutions in Europe. My current role involves line management responsibilities, oversight of projects’ scope management, and development/expansion of the programming group.

Scope management mainly involves ensuring optimal utilization of our programmers across projects, controlling the quality of deliverables, overseeing the financial health of projects, and monitoring the correct implementation of programming processes. I am also actively involved in recruiting and onboarding new team members, establishing company processes, developing standard tools, and supporting department initiatives.

An illustration of such an initiative is the internship program in the programming department I developed in 2021. During the past 3 years, sustainable partnerships with 3 different universities have been built, and each year, for 6 months, we welcome students aiming to discover the role of statistical programmer in the pharmaceutical industry. This program often concludes by the conversion of the internship into a permanent contract, which shows how successful it really is.

What motivated your transition from biostatistics to statistical programming? How has your background in biostatistics influenced your approach to statistical programming?

While I have a background as a biostatistician, I have always enjoyed programming. When I first started working as a statistical programmer, I realized my expertise in biostatistics was an incredible asset, especially for programming complex statistical models. I could fully understand these models and their results, detect potential issues, and easily discuss biostatistics topics such as the management of missing data with biostatisticians. Sometimes, I could even challenge them. To me, being a statistical programmer is the perfect combination of everything I like, and it allows me to play a central role in the analysis of clinical trials.

How have your managers or colleagues at Cytel supported your professional growth since you joined the company? From your perspective, what specific aspects of Cytel’s culture or environment contribute to making it an exceptional place to work?

I have been fortunate to receive close mentorship from my managers since I began my journey at Cytel. It empowered my continuous professional growth. My current manager Nicolas Rouillé (Senior Director Statistical Programming) always looks for opportunities to get me more involved in my role at Cytel. His trust and willingness to share his experience across various fields gave me the confidence to succeed in any challenge I might face. In turn, I strive to apply the same principles with my direct reports, to strengthen the team and the organization as a whole.

At Cytel, we foster a strong team spirit and have numerous experts across all functions. I’m always grateful to work in an environment where, every day, people demonstrate enthusiasm, courage, collaboration, and commitment to achieving a common goal — delivering high-quality results to clients and actively contributing to the improvement of patient care.

Could you discuss Cytel’s integrated project management approach, which aims to synchronize delivery among data managers, biostatisticians, and programmers? How has this approach benefited our clients?

Cytel provides end-to-end biometric solutions, including data management, programming, and biostatistics services. One example of the automation of cross-functional delivery is the implementation of the standard data library and CDASH during the eCRF design/development, and the generation of SDTM template programs. When eCRFs comply with CDASH standards, the corresponding STDM mapping in CDISC standards can be automated. The main benefit is that it enables us to increase our compliance with industry standards and improve the efficiency from data collection to reporting. CDISC compliance for analysis datasets is a key requirement from health authorities at the submission stage, which is why this automation benefits our clients directly.
Another cross-functional automation we developed at Cytel involves a tool that generates template output programs from standard mock shells and metadata. This collaboration between the biostatistics and programming teams has resulted in the production of high-quality deliverables.

Could you provide an example or project that illustrates how we deliver added value for our clients?

Recently, a client requested us to handle health authority questions for one of their Phase III oncology studies. We were contracted for biostatistics and programming services on very short timelines — what we call a rescue study. The scope wasn’t straightforward either, as we had to produce six complex efficacy ADaMs including multiple imputation rules and around 70 unique efficacy outputs presenting different statistical models.

We were able to successfully deliver a high-quality package to the client, on time, and received only minimal comments. Following this, the client informed us that they received a positive CHMP opinion for this submission. They expressed their gratitude for our collaboration and support during the submission process.

What strategies do you employ to ensure the quality and accuracy of deliverables, particularly when working on projects with tight timelines or complex data sets?

My team is composed of individuals with different seniority and experience levels, from junior programmer to associate director. When a complex project with tight timelines arises, my priority is an optimal resource assignment based on the availabilities as well as individual experience and knowledge. Sometimes a switch of resources across projects will lead to the best team setup.
When working on the project, we pay a lot of attention to writing specifications and performing programming and biostatistical review of ADaM datasets with a focus on the computational methods of complex derivations. We perform advanced quality controls or cross-checks against other outputs to ensure the accuracy of the results. Any findings related to data, such as missing data, data issues, or specific study data scenarios that can impact study results are shared with the client before proceeding with the delivery. It’s crucial to be proactive in these cases.
Lastly, the strong collaboration across biometric line functions is essential to delivering quality to clients, especially when timelines are short.

What combination of knowledge, skills, and technical competencies is essential for individuals to succeed as statistical programmers at Cytel? What qualities do you look for when hiring new members for your team?

Obviously, technical skills are incredibly important. We pay a lot of attention to the candidate’s proficiency in statistical programming languages and their experience in clinical data and industry standards. For senior roles, we also dive into their experience as team lead, which can include several topics of interest like resource assignments, quality controls, budget awareness and management, and communication with internal or external stakeholders.

In addition, we also assess the motivation of the candidate and their appetite to learn. This can easily counterbalance a potential lack of technical skills or experience. As hiring manager, I’m also very focused on interpersonal skills and the mindset of the candidate. Skills such as self-organization, proactivity, multi-tasking, and/or strong adaptability are ones I look for.

What advice would you give to aspiring statistical programmers or individuals aiming for roles within the field?

I would advise to first familiarize yourself with clinical trial fundamentals such as different phases of clinical trials, study designs (e.g., randomized controlled trials, observational studies), and endpoint definitions. Understanding the clinical trial process is crucial for effective programming. Additionally, studying the regulatory framework surrounding clinical trials, including Good Clinical Practice (GCP) and ICH guidelines, is essential. This knowledge is key for compliance and data integrity.

Then, it’s important to learn a relevant programming language such as SAS or R and gain a solid understanding of biostatistics and the statistical methods commonly used in clinical trials, such as survival analysis, mixed models, and meta-analysis. Acquiring in-depth knowledge of programming standards used in pharmaceutical industry such as CDISC standards would also be a plus.
However, do not forget to develop your soft skills. Good communication skills, team spirit, collaboration, and problem-solving skills are vital in programming roles.

My last piece of advice to candidates is to look for internships or entry-level positions that provide exposure to clinical data analysis or programming. Real-world experience is invaluable.

Lastly, what are your main interests outside of work?

I like spending time with my family. I have two young kids, a nine-year-old and a six-year-old. My wife and I like to visit new places with them, especially European cities. We also like to hike, and since the Basel area is at the intersection of three countries — France, Germany, and Switzerland — we have plenty of good spots to enjoy the fresh air.

I also like spending time in my garden, I play football with my former Novartis colleagues, and regularly go to the gym. I’m turning 40, so staying in shape is becoming a serious objective!

Thank you, Guillaume, for sharing your experience with us!

In this latest edition of our Career Perspectives series, we had the privilege of interviewing Ludivine De Marans, Statistical Programmer, based in our Geneva office. Ludivine shares her journey from statistician in the insurance industry to statistical programmer at Cytel; what is unique about the pharmaceutical sector from the perspective of a statistical programmer; and what key skills and qualities are important for those interested in working in the field.

Can you give us a little background on your career and your professional journey so far? What inspired you to pursue a career as a statistician/statistical programmer?

I’ve always had a passion for mathematics, and that’s where it all began. After completing my MSc in Mathematics, Computer Science, and Statistics, I started my career as a Statistician at an insurance company in France. Although my title was “Statistician,” the role combined statistical analysis and programming, whereas at Cytel, and the pharmaceutical sector, these roles tend to be split up. After five years of working within that field, I started working for Cytel as a Statistical Programmer.

What prompted your decision to transition into the pharmaceutical industry, and what attracted you to Cytel specifically?

I was looking to relocate from France to Geneva and came across an opportunity at Cytel. Although I wasn’t familiar with the pharmaceutical industry, I had five years of experience with SAS, the same software commonly used in pharma, so I decided to apply.

The shift to the pharmaceutical industry intrigued me because of the meaningful nature of the work — you’re directly involved in developing new therapies that help patients globally. Cytel offered me the chance to work in a new sector and country. It was challenging at first, but it has worked out well.

Having transitioned from a role as a statistician in the insurance industry to a statistical programmer in the pharmaceutical industry, what differences have you observed?

There were several differences I didn’t expect. First, the pharmaceutical industry is highly standardized, including all the processes for statistical analysis and programming. In my previous role, I was responsible for both the programming and quality control of my work. Here, we follow a “double programming” method, where another programmer replicates your work to compare data and results. Then, a biostatistician reviews it.

Another key difference is how statistical programmers are viewed. In insurance, statisticians are more of a support function, responding to internal corporate requests. There are fewer colleagues within the company, too. At Cytel, statisticians and statistical programmers are core services for clients, and we work directly with them. It’s a different experience providing a core service to clients, compared to offering internal support within the company. This means there’s more pressure, with fixed deadlines, compared to the more flexible internal timelines I was used to.

What has been the biggest challenge you’ve faced since moving to the pharmaceutical industry?

The biggest challenge was learning about the industry itself — its terms, acronyms, and standards, which were all new to me. I wasn’t aware of how standardized and highly regulated the pharmaceutical sector is. Delivering data in a specific, industry-approved format was also a new experience.

In addition, moving from a national company in France to a global organization where English is the main language was challenging. The industry terminology was the most difficult part, and even after more than five years, I’m still learning.

Have any colleagues or mentors at Cytel been particularly helpful in helping you adjust to your role?

Yes, my colleagues were incredibly helpful, especially in getting me familiar with the acronyms and industry standards. My managers were always approachable, and I could ask questions whenever needed. I did a lot of self-studying, but knowing I had a supportive team made a big difference.

In your opinion, what key skills and qualities are important for statistical programmers? Do these vary between industries, especially in terms of soft and hard skills?

I don’t think the core skills vary much between industries. Of course, technical skills like SAS programming are essential, but there are other important qualities as well. You need to be organized, a logical thinker, and rigorous. These are skills I was able to carry over from my previous job to Cytel, and they’ve been incredibly useful here.

Can you describe a project you’ve worked on that you’re especially proud of, and explain why?

One project that stands out involved a clinical trial with numerous outputs to produce and tight deadlines. Thanks to an excellent team and strong collaboration, we managed to deliver everything on time. A few weeks later, we learned that the trial results were positive, and that this molecule could significantly improve many lives. Knowing that my work contributed to something so meaningful made me feel incredibly proud.

Do you primarily work from Cytel’s Geneva office or remotely? What’s the balance, and what factors influenced this choice?

I mostly work from the Geneva office, which was especially important when I first started. Being in the office allowed me to meet colleagues and ask questions directly, which helped me adjust. Working from home can sometimes make it harder to connect with people and get immediate answers. I live close to the office, so commuting isn’t an issue, and being in the office helps me maintain a boundary between work and personal life. That said, I do work from home occasionally.

Lastly, what are some of your main interests and hobbies outside of work?

I have two small children, so most of my time outside of work is spent with my family, which is what helps me relax the most.

Thank you, Ludivine, for sharing your experience with us!