Skill specialists

Hire R Language Data Scientists

Browse statisticians and data scientists who use R for advanced statistical modelling, clinical research, Bayesian analysis, and rigorous experimental design.

Manually reviewed
Remote worldwide
All engagement types
Statistician Biostatistician R Data Scientist Research Data Analyst Quantitative Analyst

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Stijn

Stijn

Junior
Amsterdam, Netherlands (UTC+1) Contract, Freelance Rate on request
AI & Machine Learning Engineers Data Science & Analytics
Konstantinos

Konstantinos

Junior
Athens, Greece (UTC+2) Full-time Rate on request
Engineering AI & Machine Learning Engineers
Lahiru Nuwan

Lahiru Nuwan

Senior
Colombo, Sri Lanka (UTC+5:30) Full-time, Part-time Rate on request
AI & Machine Learning Engineers Data Science & Analytics
Raza

Raza

Mid-Level
Karachi, Pakistan (UTC+5) Full-time, Part-time Rate on request
AI Product & Strategy Automation & AI Workflows
Soumyabrata Banerjee

Soumyabrata Banerjee

Mid-level
Full Time, Part Time Rate on request
AI & Machine Learning Engineers
Vesa

Vesa

Senior
Tbilisi, Georgia (UTC+4) Freelance, Contract Rate on request
Data Science & Analytics MLOps & AI Infrastructure
Aleônia

Aleônia

Senior
Recife, Brazil (UTC-3) Freelance, Contract-to-hire Rate on request
Data Science & Analytics
Aria Gheibihayat

Aria Gheibihayat

Senior-level
Full Time, Contract Rate on request
AI & Machine Learning Engineers Data Science & Analytics
Arnav Sharma

Arnav Sharma

Senior-level
Contract, Full Time Rate on request
AI & Machine Learning Engineers Data Science & Analytics
Reid Haefer

Reid Haefer

Senior-level
Full Time, Part Time Rate on request
Data Science Data Science & Analytics
python r sql gis geospatial +5

Hiring guide

Why companies hire R experts

R remains the preferred language for statistical computing, research, and academia. Data scientists who use R professionally are often stronger on statistical rigour, experimental design, and interpretable modelling than their Python-only counterparts.

Popular projects

  • Design a rigorous A/B test and analyse results with confidence
  • Build statistical models for clinical trial or biostatistics analysis
  • Develop Bayesian forecasting models for business planning
  • Validate AI model outputs with proper statistical significance testing

What to look for

  • Deep statistical knowledge (beyond basic regression)
  • Experience with Tidyverse, ggplot2, and the R data science ecosystem
  • Ability to communicate statistical results to non-technical stakeholders

Frequently asked questions

Should I hire an R or Python data scientist?

R is stronger for statistical rigour, research workflows, and certain regulated domains (clinical, academia). Python is better for production ML systems and LLM integration. For pure data science and analytics, both are valid — the best choice depends on your team's existing stack.

Can R engineers also produce charts and reports for business stakeholders?

Yes. R Markdown and Quarto allow R engineers to produce publication-quality reports and interactive dashboards using ggplot2 and Shiny. For research-heavy organisations, R-based reporting is often cleaner than Python alternatives.

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