The past couple of years have delivered a paradox for STEM talent in the U.S. Despite macroeconomic headwinds prompting notable job cuts at employers from Big Tech to Big Pharma, science- and engineering-focused firms still struggle to find the specialized expertise they need. Recent Indicators reports from the National Science Board (NSB) describe an “accelerating science, technology, engineering, and math (STEM) talent crisis,” citing chronic shortfalls in critical areas such as advanced manufacturing and biotech research—even as certain tech-heavy occupations (e.g., traditional front-end or back-end developer roles) have seen an oversaturation of candidates.

[Updated on January 12 with additional data]

The broader workforce is poised to see one of the largest shakeups in recent memory. According to the WEF’s Future of Jobs Report 2025, while 170 million new jobs are expected to be created by 2030, 92 million current jobs may be displaced.

Meanwhile, the NSB notes that the U.S. remains heavily reliant on foreign-born talent—especially from China and India—to fill roles in AI, semiconductors, and biotechnology. China has already eclipsed the United States in several scientific benchmarks, including its share of top-cited research papers and international patent applications. According to a recent Nature feature, China’s R&D spending is poised to match U.S. levels by 2030. The same publication ranked the Chinese Academy of Sciences at the top of global research institutions, with a 2023 share of 2243.22—nearly double that of second-place Harvard University (1143.43). China-based organizations also make up a growing share of top research organizations.

For U.S. employers grappling with intensified global competition and a limited domestic pipeline for specialized talent, the result is a sharp mismatch. Even as fresh cohorts of developers saturate some software roles, advanced positions in semiconductors (despite significant hardware layoffs), biotech, and other technology segments often remain understaffed.

Against this backdrop, our review of roughly 1,000 active STEM job postings—which also draws on data from agencies like the NSF and the New York Fed—reveals six recurring “must-have” skill clusters for R&D and STEM roles in 2025. While the exact mix of required competencies differs across industry niches (e.g., biotech vs. semiconductor vs. advanced manufacturing), these skill clusters consistently appear in job postings for R&D settings everywhere from biotech labs and semiconductor factories to DevOps teams and advanced research centers.

Cluster	Primary Domains	Key Skills/Focus
1. Research and data analysis	Healthcare R&D Life Sciences R&D	Python, Data Analysis, Bioinformatics Statistical Modeling, ML
2. Product/software dev for R&D	Healthcare Product Dev Eng. Design & Dev	AWS Cloud Git/Version Control Testing Frameworks Programming (Python, C++)
3. CAD-driven engineering	Eng. & Mfg (Design) Healthcare Devices	CAD Tools (AutoCAD) Prototyping ISO/Quality Systems
4. Quality and regulatory	Eng. & Mfg (Quality & Regulatory) Life Sci Ops Technical & Ops (Validation)	ISO/GxP Compliance Documentation Protocols Qualification/Validation
5. Clinical operations	Healthcare Clinical Life Sci Clinical Ops	Patient Care Protocols Lab Services AWS Use in Clinical Settings
6. Infrastructure and systems	Technical & Ops (Infrastructure) Some Healthcare/Eng. Operations	AWS Architecture Security & Monitoring Automation/CI/CD

A deeper dive

Below, we explore how these core capabilities shape modern R&D roles.

1. Data analysis and programming

In numerous R&D environments—from biotech and healthcare to engineering and advanced manufacturing—data analytics and programming remain top priorities for STEM employers. Tools such as Python, R, and various machine learning frameworks appear regularly in job listings, while SQL and SAS also maintain a presence in academic and clinical research contexts. These roles apply computational methods to tasks ranging from genomic data analysis in computational biology to process optimization in manufacturing. National laboratories and forward-learning research organizations are more likely to emphasize experience with machine learning frameworks (e.g., TensorFlow and PyTorch) for complex data analysis projects. For instance, a postdoctoral position at Argonne National Laboratory requires experience in deep learning with frameworks like PyTorch or JAX and scaling models on GPU-based machines. The trend is spilling into a growing number of R&D domains including national lab listings for research software engineering roles. Machine Learning/AI appears in 73 positions (14.7% of total listings) while compensation for senior AI/ML roles among the best-compensated in the dataset reaching close to $300,000 in some cases.

Skills such as data analysis, statistics, math and programming aren’t only valuable for their own sake. According to WEF, analytical thinking writ large remains the most sought-after core skill among employers, with seven out of 10 companies considering it essential in 2025.

2. Cloud and infrastructure

Cloud computing has long since become de rigueur in many research contexts and this reality was reflected in STEM job listings. Several job postings mentioned expertise in cloud and containerization. Security and compliance requirements stand out in healthcare-focused roles, with 41% of research-oriented positions emphasizing secure protocols. Research hospitals remains a prominent employer, posting multiple specialized cloud positions (including Cloud DevOps Engineers and Research Scientists). From a technical skills perspective, AWS and Python continue figure prominently in postings followed by Azure adoption. Compensation data underscores the premium placed on cloud expertise: one senior technical position for Disaster Recovery Engineers command mentioned a salary range of $126,610–$215,270. A specialized lead engineering role (e.g., Identity Services) offered $152,000–$190,000 while data engineering roles had salary ranges in the ballpark of $120,000–$128,000.

WEF’s The Future of Jobs Report 2025 indicates that AI and information processing technologies will have the biggest business impact, with 86% of organizations expecting transformation in these areas by 2030.

3. CAD and design tools

Physical and product-focused R&D heavily relies on CAD software and integrated design tools for prototyping and product development. Those realities were reflected in job descriptions with general CAD competency having 264 mentions across the dataset. Manufacturing and simulation capabilities were recurring themes with a number of positions requiring integrated manufacturing workflow expertise and a few positions specifically calling for FEA simulation capabilities. For instance, a large medical device manufacturer lists a principal engineering position offering “$126,000-166,800 for candidates with advanced industrial engineering experience.” Another position at a legacy aerospace company emphasizes “specialization in low volume, high mix manufacturing and supply chain management” with production engineering roles starting at $97,000.

4. Data-driven laboratory and experimental techniques

Lab work is evolving in pharma and biotech research as well as in clinical lab settings and niche electronics testing as organizations focus more on data analysis platforms and automation tools. Modern scientists may transition from preparing PCR assays to interpreting large-scale sequencing data in bioinformatics suites. Key technical clusters include molecular and cellular techniques like PCR and sequencing, data integration using bioinformatics platforms and experimental design software, and adherence to quality standards such as GMP and GCP, alongside proficiency in rigorous laboratory protocols. For instance, in the job postings, one prominent research hospital was looking for candidates with experience working with high-throughput molecular techniques integrated with bioinformatics analysis platforms. A number of positions required both laboratory expertise and digital workflow integration, including proficiency in Python or R.

5. Cross-functional communication and documentation

Technical documentation proved to be one of the most common skills mentioned in our dataset, noted in about 3 of every 10 job postings; meanwhile, roughly one-third of listings reference regulatory compliance or ISO standards. Nearly one-quarter of the postings emphasize the importance of cross-functional or collaborative workflows—some even cite specific “interdisciplinary project requirements” tying together data scientists with bench researchers in biotech settings or mechanical engineers with software developers in robotics. A number of listings in lab services and semiconductor settings mentioned cross-functional integration while a prominent medical device firm accentuated protocol development and integration with quality management systems. Across listings, robust documentation and cross-functional communication remain priorities in modern R&D and product development.

6. Automation and robotics systems

As industries push for higher efficiency and reduced human error, industrial automation and robotics continue to grow in importance in R&D labs and manufacturing floors. In the dataset, about 13% reference these capabilities explicitly—ranging from PLC programming in chemical processing (appearing in over 30 postings) to advanced robotics integration in assembly lines or high-throughput lab screening.

Among the jobs mentioning automation, several positions emphasize IoT-based control systems, SCADA architectures, or industrial control systems (ICS). In biotech R&D, for instance, automated pipetting robots can significantly speed up assay workflows, while advanced sensor arrays stream data to cloud-based dashboards for real-time monitoring. On a larger scale, some postings reference “process optimization systems,” referring to the development of feedback loops that can potentially tie robotics, data analytics, and machine learning together under one umbrella. As a result of such convergence, a single robotics engineer might now need experience programming both PLC logic and cloud-connected analytics platforms, while a process control specialist could require a grounding in mechanical systems, user interface design, and cybersecurity best practices.

Among job postings reviewed, about 40% of those focused on automation were leadership or management related while just over one-third (35%) were focused on technical Implementation and a quarter focused on research. A job posting at a large medical device company had requirements related to regulatory knowledge, interdisciplinary expertise, and experience managing large-scale deployments. Meanwhile, a listing at a national lab mentions the need to work with scores of visiting researchers along with the need to support large-scale R&D infrastructure and multi-stakeholder coordination.

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Future Workforce Implications

The Future of Jobs Report 2025 estimates that “if the world’s workforce was made up of 100 people, 59 would need training by 2030.” This underscores the critical importance of continuous skill development in STEM fields.**