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DataAnnotation
Posted 127 days agoVerified live 1d ago

Epidemiologist - AI Trainer

Brief overview

Remote
UndergradOr in progress
2+ yrsMinimum
3 green cardsCertified filings
Statistical analysisPredictive modelingScientific reasoningData-driven insightsForecastingExperimental analysisOptimizationStatistical inferenceCoding (analytical code)A/B testingHypothesis testingRegressionClassificationTime-series forecasting

About the company

DataAnnotation logo
DataAnnotationdataannotation.tech

Welcome to DataAnnotation! We pay smart folks to train AI.

Visa sponsorship history

2 years sponsoring, last filed FY2024

Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.
3PERM certified
$116,000median wage / yr
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
20231
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
20243
Top sponsored roles
Senior Solutions Consultant
Sponsored employees from
ChinaUnited Kingdom

Job description

Summary

DataAnnotation is seeking an Epidemiologist - AI Trainer to join their team and contribute to developing cutting-edge AI systems while enjoying the flexibility of remote work. The role involves evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback to enhance AI models' reasoning capabilities.

Responsibilities

  • Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity
  • Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference
  • Write clear technical explanations and well-documented analytical code
  • Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning

Skills

  • 2+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field
  • Some coding experience required, with comfort writing and reviewing analytical code end-to-end
  • Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time-series forecasting)
  • Fluency in English (native or bilingual level) with strong writing skills
  • A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus
  • Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise)

Qualifications

Must Haves

  • 2+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field
  • Some coding experience required, with comfort writing and reviewing analytical code end-to-end
  • Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time-series forecasting)
  • Fluency in English (native or bilingual level) with strong writing skills

Nice to Haves

  • A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus
  • Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise)

Benefits

  • Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
  • Flexible schedule: choose which projects you take on and when you work.
  • Impact: help shape the future of AI systems built to reason about data and analytics.

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