Friday, November 14, 2025 - 12:00pm to 1:00pm ET
Event Page: NISS Virtual Career Panel: Statistical Careers in BioPharma | National Institute of Statistical Sciences
This virtual career fair featured a panel on statistical careers in biopharma, with panelists discussing their experiences in clinical trials, commercial roles, and drug development across various pharmaceutical companies. Speakers shared insights on the importance of cross-functional collaboration, statistical tools and methods, and the role of statistics in decision-making and healthcare. The discussion covered career opportunities, skills requirements, and industry transitions, emphasizing the value of quantitative science in pharmaceuticals and the potential for remote work in various statistical roles. Our Moderator for this session was Dr. Richard Baumgartner, from Merck's Biostatistics Department, who introduced our webinar on statistical careers in biopharma featuring panelists Dr. Zhenzhong Wang at Eli Lilly, Dr. Oluyemi Oyeniran at Johnson & Johnson and Dr. Kaihua Ding at AstraZeneca.
Clinical Trials Data Analysis Challenges
Dr. Wang, a Senior Advisor of Statistics at Eli Lilly, shared his experience working in the cardiometabolic health field, overseeing early-phase studies in cardio-renal space and supporting multiple compounds in Phase 1 and 2 trials. He emphasized the importance of cross-functional collaboration in biopharma, highlighting the need to work with various teams to ensure timely and efficient study delivery.
Dr. Wang discussed his role in clinical trials, focusing on data analysis, visualization, and safety reviews. He highlighted the challenges in defining endpoints for Phase II and Phase III studies, particularly in heart failure trials. He then emphasized the importance of cross-functional collaboration in biopharma, noting that statisticians must be familiar with medical background information to build trust and persuade team members. He also touched on the need for innovation in study design and analysis methods.
Portfolio Strategy and Statistical Impact
The discussion focused on the importance of understanding portfolio strategy and team members' roles across different functions. It was emphasized that statisticians need to identify impactful work that advances drug development and pipeline progress, rather than just focusing on statistical innovation. The role of statistics in decision-making was highlighted, with a focus on providing objective and data-driven insights. Panelists also discussed the potential for creating tools, such as visualization and AI tools, to improve efficiency in a widely expanded pipeline.
Biostatistics Career and Impact Strategies
The meeting focused on strategies to enhance decision-making and study design in biostatistics, emphasizing collaboration with non-stat researchers and publishing in non-stat journals to increase impact. Skills and experiences highly valued in the field were outlined, including being smart, hardworking, eager to learn, and capable of adopting new things quickly, along with AI and machine learning capabilities, consulting experience, and strong communication skills. Opportunities for full-time employment, internships, and academic collaborations were discussed, and the presentation concluded with an overview of quantitative science applications in pharmaceuticals, particularly in drug development.
Statisticians' Role in Healthcare Drug Development
The discussion focused on the role of statisticians and quantitative scientists in healthcare and drug development. The speakers explained how statistics provides insights for informed decision-making, quantifies risk, and enhances health outcomes by supporting both business and scientific decisions. They outlined the drug development cycle, from discovery through regulatory approval to market assets, and detailed how statisticians contribute at various stages, including discovery, preclinical research, clinical trials, and manufacturing.
Statistical Roles in Drug Development
The discussion covered statistical roles in pharmaceutical companies and contract research organizations, emphasizing the need for advanced specializations in biostatistics, data science, and bioinformatics beyond foundational quantitative science degrees. The speaker highlighted various statistical tools used in drug development, including survival analysis, Bayesian methods, and time series, while noting that J&J primarily uses R software. They also introduced emerging trends in drug development, such as generative AI for molecular design, digital trends in clinical trials, and the use of biomarkers in discovery and preclinical research.
AI in Pharma: Skills and Opportunities
The speaker discussed the applications of AI and machine learning in pharmaceuticals, emphasizing the importance of both technical and soft skills for statisticians. They highlighted the need for effective communication, collaboration, and adaptability when working with cross-functional teams. The presentation concluded with advice on exploring internship opportunities, building software proficiency, and networking within the industry through organizations like the American Statistical Association.
Statistical Roles in Pharma Business
Kai Ding, who works at AstraZeneca's biopharmaceutical business unit in Wilmington, Delaware, discussed his experience working in a commercial and medical affairs role. Unlike the previous speakers who focused on clinical trials, Kai explained how his statistics background is applied in a commercial context, supporting various business activities. He described the typical structure of pharmaceutical companies, which often have three main business units: biopharmaceutical, oncology, and research, and highlighted the option for statisticians with PhDs to work in a center of excellence, either in clinical trials or in commercial roles as analysts or data scientists.
Pharmaceutical Career Paths Discussion
The discussion focused on career paths in pharmaceutical Center of Excellence organizations, where speakers explained that while statistics backgrounds are common, roles in commercial decision-making can be entered with various academic backgrounds, emphasizing quantitative skills and presentation abilities. The speaker shared their experience at AstraZeneca, noting that while their organization isn't currently hiring, they're open to referrals, and concluded by transitioning to a Q&A session with Dr. Wang.
Biostatistics Career Transition Insights
The panel discussed various topics related to biostatistics and career transitions in the industry. They addressed the use of SAS vs. R for analysis, noting a shift from SAS to R at J&J due to cost considerations. The panel also provided advice for a PhD student interested in clinical trial roles, emphasizing the importance of highlighting relevant skills and experience in resumes and cover letters. They discussed the transition from academic research to biopharmaceutical industry roles, suggesting that while the perspectives may differ, the skills are transferable.
Academic to Industry Research Transition
The discussion focused on the challenges of transitioning from academic research to industry work, particularly in pharmaceuticals. Participants highlighted the shift in priorities from producing perfect research to delivering impactful results, emphasizing the need for timely decision-making and collaboration across large teams. They also discussed how academic accomplishments, while valuable, may not align with industry expectations, suggesting that a more industry-focused resume might be beneficial for job seekers in this sector.
Biopharma Career Opportunities for Stats and Actuaries
The discussion focused on career opportunities in biopharma for statisticians and actuaries. It was explained that while knowledge of CDISC and ADAM frameworks is important for clinical trial roles, it's not strictly required for other functions like commercial or preclinical drug discovery. For actuaries with a background in risk analysis, it was suggested that their skills could be well-suited for market access roles rather than clinical trials, as pharmaceutical companies still require risk management capabilities in areas like medical affairs and payer relations. The conversation concluded with information about the company's extensive U.S. presence, suggesting that geographic constraints might not always require relocation for remote full-time positions.
Pharmaceutical Career Opportunities Overview
The webinar focused on career opportunities in the pharmaceutical industry, with discussions about remote work possibilities and various job types, including full-time positions, internships, and academic contracts. Panelists explained that while some roles can be fully remote, in-person visits are often required for career development and important meetings. They emphasized that hiring processes vary by company but typically involve multiple interviews and presentations, with opportunities available year-round rather than during a specific season. The panelists also advised students to explore multiple software tools beyond SAS, consider attending on-campus career fairs, and directly apply through company websites for the best chances of finding pharmaceutical industry jobs.
Acknowledgements
NISS gratefully acknowledges the contributions of our distinguished moderator and panelists for sharing their time, expertise, and career insights in service of the statistical community. We extend our sincere thanks to Dr. Richard Baumgartner of Merck, who served as moderator and guided a thoughtful and engaging discussion. We also thank our panelists—Dr. Zhenzhong Wang of Eli Lilly, Dr. Oluyemi Oyeniran of Johnson & Johnson, and Dr. Kaihua Ding of AstraZeneca—for their informative perspectives on statistical careers across clinical development, commercial strategy, and drug development. Their commitment to mentoring and advancing quantitative science continues to strengthen and inspire the broader statistics community.