Hiring in statistical programming is changing. As clinical trials become more complex and regulatory expectations continue to rise, the industry needs programmers with expertise beyond SAS. Automation, real-world evidence (RWE), and evolving compliance standards are reshaping hiring priorities, and companies that do not adjust their recruitment strategies will struggle to keep up.

Pharma, biotech, and CROs compete for programmers who can manage regulatory compliance, standardize data, and support evolving trial designs. Companies need professionals who can work across biostatistics, data management, and regulatory teams to ensure submission-ready datasets. Those with multi-language proficiency, automation experience, and a strong understanding of compliance frameworks are now in the highest demand.

This guide breaks down the five key skills shaping statistical programming hires in 2025 and the roles that require them. Organizations who recognize these priorities will be best positioned to build teams equipped for the challenges ahead.

Key Sectors Driving Demand

In 2025, statistical programming is essential in several high-growth areas, particularly pharmaceuticals, biotechnology, CROs, and the integration of AI in clinical research. Three key trends are shaping hiring needs:

1. Regulatory Complexity and Data Standardization

Regulatory agencies, including the FDA, EMA, and PMDA, now require highly structured, traceable, and reproducible data for clinical trial submissions. Statistical programmers with expertise in CDISC SDTM/ADaM and audit-ready dataset preparation are in the highest demand. Failure to meet compliance standards can result in delays, additional regulatory queries, or even rejection of drug approvals.

2. Advanced Trial Designs and Real-World Evidence (RWE)

The rise of adaptive clinical trials, decentralized studies, and real-world data integration is reshaping statistical programming workflows. By mid-2025, over 70% of new drug applications will incorporate RWE, increasing the need for programmers who can manage complex datasets beyond traditional clinical trial structures. Biotech firms and CROs are actively recruiting programmers who can integrate electronic health records, patient registries, and post-market surveillance data into regulatory submissions.

3. Automation and AI-Driven Programming

Automation is reducing manual programming work, but it is also increasing the need for statistical programmers who can implement, validate, and oversee AI-driven workflows. Companies investing in automated statistical workflows and real-time compliance monitoring need programmers with R, Python, and AI integration experience to improve efficiency while maintaining regulatory integrity.

As these industry shifts take hold, hiring managers in pharma, biotech, CROs, and AI-driven clinical research must focus on statistical programmers with the right mix of regulatory expertise, technical skills, and adaptability.

The 5 Most In-Demand Skills for Statistical Programmers 

Statistical programmers are central to data integrity, regulatory submissions, and trial efficiency, but the expertise required in 2025 is shifting. Companies are not just looking for technical proficiency—they need programmers who understand automation, regulatory frameworks, and multi-source data integration to manage increasingly complex clinical trials.

This shift is creating a competitive hiring environment. As demand for statistical programmers grows, companies that focus on securing professionals with the right mix of technical, regulatory, and analytical expertise will be in the strongest position to keep up with evolving clinical research needs. The following five skills are now essential when hiring statistical programmers.

1. Regulatory & Compliance Expertise

Regulatory agencies are setting higher expectations for clinical trial data. The FDA, EMA, and PMDA now require structured, traceable, and submission-ready datasets, making statistical programmers with CDISC SDTM/ADaM expertise more important than ever. Without them, companies face delays, additional regulatory queries, or outright rejection of drug approvals.

In oncology and rare disease trials, regulatory scrutiny is particularly high. The FDA’s Real-Time Oncology Review (RTOR) program allows for faster approvals but only for companies with compliant, well-structured datasets. Similarly, as more companies submit data across multiple global markets, statistical programmers must be equipped to handle differing regulatory frameworks and ensure consistency across submissions.

A study analyzing data processing methods found that error rates in clinical trial data ranged from 0.02% to 27.84%, depending on the method used. These errors can lead to significant delays and complications in regulatory submissions, highlighting the need for meticulous data management and standardization.

Roles where this skill is required:

• Regulatory Submission Programmer – Ensuring datasets meet submission requirements for global agencies.
• CDISC SDTM/ADaM Specialist – Standardizing trial data for compliance and approval efficiency.
• Principal Statistical Programmer – Leading regulatory programming strategies across trial phases.

2. Multi-Language Proficiency (Beyond SAS)

SAS remains widely used in clinical trials, but hiring only SAS programmers is becoming a limitation. Companies are now seeking statistical programmers with R and Python expertise to support automation, machine learning, and real-world data integration.

The shift is already happening. Over 60% of statistical programming job postings in 2024 required experience with R or Python, reflecting the growing demand for flexibility beyond SAS. R is now widely accepted in regulatory submissions, particularly in real-world evidence (RWE) studies, while Python is increasingly being used for automation and predictive analytics.

• Hiring managers should prioritize statistical programmers who:
• Have SAS experience but can also code in R and Python.
• Can integrate automated workflows into trial data analysis.
• Understand AI-driven analytics and machine learning models.

Roles where this skill is required:

• Senior Statistical Programmer – Supports multi-language programming in clinical trials.
• SAS Programmer – Develops and validates SAS programs for clinical trial data analysis.
• Lead Statistical Programmer – Manages programming across multiple languages and platforms.

3. Real-World Evidence (RWE) & Adaptive Trial Design Knowledge

Clinical trials no longer exist in isolation. Regulatory bodies, investors, and payers are demanding more real-world data (RWD) to support approvals and pricing decisions. A study analyzing FDA approvals from January 2019 to June 2021 found that 85% of new drug and biologics license applications incorporated RWE in some form, with the proportion increasing each year. This trend underscores the growing demand for statistical programmers adept at managing complex, multi-source datasets beyond traditional clinical trial structures.

This is particularly relevant in precision medicine and rare disease research, where real-world data is critical in demonstrating treatment efficacy. Biotech firms, CROs, and pharmaceutical companies increasingly seek programs skilled in handling electronic health records (EHRs), patient registries, and post-market surveillance data.

Hiring managers should focus on programmers with direct experience in structuring regulatory-compliant RWE datasets.

Roles where this skill is required:

• Lead Statistical Programmer – Managing real-world data integration in trials.
• RWE Data Analyst – Structuring and analyzing real-world datasets for regulatory submissions.
• Clinical Data Scientist – Aligning trial data with real-world patient outcomes.

4. Automation & AI Integration in Programming

Automation is changing how statistical programmers work, reducing repetitive coding tasks and improving data accuracy in clinical trials. Instead of replacing programmers, automation supports faster dataset generation, validation, and submission preparation, allowing teams to focus on more complex problem-solving.

A 2023 study on clinical trial data collection, The Smart Data Extractor: A Clinician-Friendly Solution to Accelerate and Improve Data Collection During Clinical Trials, found that manual data entry across 79 patients resulted in 163 errors, whereas the implementation of an automated system reduced this number to 46. The findings demonstrate the significant role automation plays in enhancing accuracy and efficiency in clinical trial data management.

As clinical datasets continue to grow and regulatory expectations increase, automation supports data standardization, real-time quality control, and submission readiness, helping to minimize errors and prevent delays in regulatory submissions.

Hiring managers are increasingly looking for statistical programmers who can apply automation to improve efficiency while ensuring compliance with regulatory requirements. This is especially valuable in pharmaceutical companies, CROs, and biotech firms, where automation is improving data integrity and submission timelines.

Roles where automation is becoming increasingly valuable:

• Senior Statistical Programmer – Implements automation for data processing and quality checks.
• Principal Statistical Programmer – Oversees programming strategies that incorporate automation.
• SAS Programmer – Develops macros and scripts to standardize dataset generation.

5. Cross-Functional Collaboration & Leadership

Statistical programming is no longer a siloed function. As clinical trials become more complex, statistical programmers must work closely with biostatisticians, regulatory teams, and clinical operations to ensure datasets are structured correctly and submissions are prepared efficiently.

Hiring managers are increasingly prioritizing candidates who can bridge the gap between programming and broader clinical teams. The ability to interpret regulatory expectations, collaborate on trial designs, and effectively communicate findings is now as important as technical expertise. Companies investing in statistical programmers with leadership capabilities are seeing faster regulatory approvals, smoother trial execution, and reduced compliance risks.

As decentralized trials expand, cross-functional collaboration is becoming a hiring priority, particularly for roles that oversee programming strategies and ensure alignment across regulatory and clinical functions.

Roles where this skill is required:

• Associate Director of Statistical Programming – Managing teams across regulatory, statistical, and clinical functions.
• Principal Statistical Programmer – Leading data standardization and submission efforts.

What This Means For Your Organization

The expectations placed on statistical programmers are higher than ever. Companies need experts who can ensure regulatory compliance, integrate automation into workflows, and structure complex clinical trial data efficiently. The challenge is that demand is growing faster than supply, particularly for programmers who can work across multiple programming languages and adapt to changing regulatory requirements.

Regulatory agencies are pushing for greater statistical programming transparency, standardization, and automation. Clinical trials generate increasingly complex datasets, and ensuring submission readiness requires statistical programmers who can structure, validate, and report data in compliance with global regulatory frameworks. 

For hiring managers, this means acting strategically. Waiting too long or relying on outdated hiring processes can result in delays, compliance risks, and difficulty securing the right talent.

Key Hiring Considerations in Statistical Programming:

• Competition for talent is intensifying: Statistical programming jobs require a combination of technical, regulatory, and automation expertise. Delays in hiring mean missing out on top candidates.
• Balancing permanent and contract hires is essential: Companies need a clear approach to workforce planning to ensure long-term expertise while maintaining flexibility for high-demand projects.
• Generalist hiring strategies do not work: Statistical programming requires a specialist approach to recruitment to assess technical and compliance expertise effectively.
• Hiring must anticipate future challenges: Programmers who can apply automation, adapt to regulatory shifts, and collaborate across clinical functions will be critical for long-term success.

How Hiring Managers Can Stay Ahead

The Demand for Hybrid Skills Is Outpacing Supply

Statistical programmers today are expected to do more than code in SAS. The need for professionals who can manage regulatory submissions, automate programming workflows, and integrate real-world data into trial analysis is growing incredibly quickly. However, there are not enough candidates with this combined expertise.

Hiring managers need to recognize that the most in-demand programmers are not on the market for long. Companies that wait too long to hire or fail to adjust hiring expectations will struggle to secure candidates with the right mix of programming and compliance experience.

Balancing Permanent and Contract Hires

Many pharmaceutical and biotech companies are using contract statistical programmers to manage submission deadlines, automation projects, and large-scale data validation, while keeping permanent hires for leadership and compliance oversight.

• Permanent hires are essential for maintaining regulatory expertise, team leadership, and ongoing trial development.
• Contract hires provide flexibility for high-demand projects, particularly in regulatory submissions and data standardization.

A well-structured hiring strategy ensures compliance remains a priority while allowing teams to scale effectively.

The Role of Specialist Recruitment in Statistical Programming

Recruiting statistical programmers is not as simple as hiring for general IT or data science roles. Regulatory frameworks, automation, and statistical methodologies all require specialized knowledge. Generalist hiring teams often fail to evaluate technical and compliance expertise correctly, leading to hiring mismatches.

Working with recruiters who specialize in statistical programming and clinical trials helps hiring managers:

• Reduce hiring time by identifying programmers with direct experience in biometric data validation and regulatory compliance.
• Ensure candidates meet industry standards for statistical programming jobs, rather than relying on general technical assessments.
• Secure automation-ready programmers who can support AI-driven validation and data standardization projects.

Future-Proofing Statistical Programming Teams

Statistical programming in clinical trials is shifting. Companies that only hire for immediate needs will find themselves behind as automation, regulatory expectations, and clinical trial methodologies continue to change. Hiring managers must anticipate future skill gaps to ensure their teams can handle regulatory shifts and automation advancements without disruption.

A future-ready statistical programming team should have:

• Automation and validation expertise: Programmers who can apply automated quality control and submission-ready workflows.
• Regulatory adaptability: Candidates who stay ahead of global compliance requirements and can standardize biometric data for multi-region submissions.
• Cross-functional collaboration: Programmers who can work with biostatisticians, clinical teams, and regulatory functions to ensure data integrity.

Companies that invest in the right statistical programming hires today will be positioned for greater efficiency, faster approvals, and stronger regulatory compliance.

Building Strong Statistical Programming Teams: Final Thoughts

The need for statistical programmers with expertise in regulatory compliance, automation, and multi-language proficiency is growing. Companies that prioritize these skills will be better equipped to meet submission requirements, manage evolving trial designs, and ensure data integrity.

Hiring managers must take a structured approach to recruitment, ensuring teams have the right mix of long-term expertise and flexible support. Specialist recruitment strategies are essential for effectively identifying programmers with the technical and regulatory knowledge to support clinical trials.

With demand increasing, securing statistical programming talent now will strengthen data management, improve compliance, and position organizations for success in a changing regulatory environment.

Secure the Statistical Programming Talent You Need

Since 2017, we have built a strong reputation for connecting statistical programmers, biostatisticians, and regulatory specialists with leading life science, research, and pharmaceutical organizations. Our tailored recruitment solutions ensure you have the right talent to manage regulatory submissions, data standardization, and automation in clinical trials.

With a deep understanding of biometric recruitment, our consultants support you at every stage, from identifying key hires to ensuring a smooth onboarding process. Whether you need permanent specialists or contract professionals, we can help you build a team that meets today’s demands and prepares you for the future.

Get in touch today to find out how we can support your hiring needs and help you stay ahead in statistical programming recruitment.