Skill specialists

Hire Statisticians & Quantitative Analysts

Find statisticians and quantitative analysts who bring rigorous experimental design, causal inference, and probabilistic thinking — the foundation that makes AI results trustworthy.

Manually reviewed
Remote worldwide
All engagement types
Statistician Quantitative Analyst Experimentation Scientist Data Scientist Causal Inference Researcher

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Konstantinos

Konstantinos

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

Parker

Senior
Vancouver, Canada (UTC-7) Part-time, Freelance Rate on request
Data Science & Analytics AI & Machine Learning Engineers
Aditya

Aditya

Senior
Kolkata, India (UTC+5:30) Full-time, Part-time Rate on request
AI & Machine Learning Engineers Data Science & Analytics
Stelios

Stelios

Senior
London, United Kingdom (UTC+0) Full-time, Freelance Rate on request
AI & Machine Learning Engineers NLP & Prompt Engineering
Bushra

Bushra

Senior
Kolkata, India (UTC+5:30) Full-time, Part-time Rate on request
AI & Machine Learning Engineers Data Science & Analytics
Michael

Michael

Senior
Berlin, Germany (UTC+1) Freelance Rate on request
AI & Machine Learning Engineers Data Science & Analytics
Ankush

Ankush

Mid-Level
Kolkata, India (UTC+5:30) Full-time, Part-time Rate on request
AI Training & Data Annotation NLP & Prompt Engineering
data annotation Voice AI Agents voiceflow statistics llm fine-tuning
Pooja

Pooja

Mid-Level
Kolkata, India (UTC+5:30) Full-time, Part-time Rate on request
Data Science & Analytics AI & Machine Learning Engineers
Erica

Erica

Mid-Level
Los Angeles, United States (UTC-8) Full-time, Freelance Rate on request
Data Science & Analytics Data Engineering & Big Data
Aleksey

Aleksey

Mid-Level
Belgrade, Serbia (UTC+1) Full-time, Contract Rate on request
AI & Machine Learning Engineers Data Science & Analytics

Hiring guide

Why companies hire Statistics experts

Statistics is the scientific foundation of reliable AI. Companies that hire statisticians alongside ML engineers make better decisions about model evaluation, A/B testing, causal inference, and the reliability of AI-generated insight.

Popular projects

  • Design and analyse A/B tests to validate your AI product decisions
  • Measure the real business impact of an AI feature you shipped
  • Build probabilistic forecasting models for revenue or demand planning
  • Calculate sample sizes so your experiments reach statistical significance

What to look for

  • Strong foundations in probability theory and inferential statistics
  • Experience with experimental design and A/B testing at scale
  • Knowledge of causal inference methods (DiD, IV, RDD, propensity scoring)

Frequently asked questions

Why should an AI company hire a statistician?

ML engineers build models; statisticians validate that the results are real. Without statistical rigour, AI companies risk optimising for metrics that don't reflect real-world impact — or missing insights hidden by confounding variables.

What is causal inference and why does it matter for AI?

Causal inference determines whether your AI system is actually causing the outcomes you observe, or just correlating with them. It's the difference between a model that predicts and a model that drives real business decisions — essential for pricing, recommendations, and product experiments.

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