AI Skills for Clinical & Translational Data Science Jobs
Clinical and translational roles apply models and statistics to biomarkers, trials, and real-world patient data.
From 59 live Clinical & Translational roles, within our analysis of 494 AI/ML postings · updated October 1, 2026
What Clinical & Translational roles actually do
You apply models and statistics to biomarkers, trials, and real-world patient data: finding signals, building predictive and prognostic models, and holding them to a high bar of validation.
Most-requested skills for Clinical & Translational roles
Share of the 59 live Clinical & Translational AI/ML postings mentioning each skill.
The core stack, explained
The tools that show up most in Clinical & Translational postings, and why they matter.
Who's hiring
Companies with the most open Clinical & Translational AI/ML roles right now.
Typical pay
Median-to-median disclosed salary band across these roles, where pay is posted.
What makes Clinical & Translational different
Rigor is the differentiator: statistics ranks second only to Python here, and R appears more than in most other sub-fields, with an emphasis on careful validation. ML is applied here, but the bar for methodological soundness is higher because the outputs touch patients.
How to break into Clinical & Translational
Emphasize methodological soundness: a project that handles real-world or clinical-style data carefully, with proper validation and honest uncertainty, signals the rigor these teams require.
Frequently asked
What skills do clinical & translational jobs require?
Across 59 live Clinical & Translational AI/ML roles, the most-requested skills are Python, Statistics, Bioinformatics, LLMs, R, Generative AI. Percentages for each are in the breakdown above.
How is Clinical & Translational different from general AI/ML in biotech?
Rigor is the differentiator: statistics ranks second only to Python here, and R appears more than in most other sub-fields, with an emphasis on careful validation. ML is applied here, but the bar for methodological soundness is higher because the outputs touch patients.
Do I need a biostatistics background for clinical data science?
It helps a lot. These roles weight statistics and study design heavily, and many sit close to biostatistics teams. Strong ML plus statistical rigor is the winning combination.
Find Clinical & Translational roles
Browse live clinical & translational and related AI/ML roles at top biotech and pharma companies.
Browse all jobsPart of the AI/ML Skills in Biotech guide. Explore other sub-fields: Protein Design & Structure · AI Drug Discovery & Chemistry · Genomics & Multi-Omics · Imaging & Pathology · ML Engineering & Platform