Data Science Consultant - AI Trainer
location_on880 P, 880, P Street Northwest, Shaw, Logan Circle/Shaw, Ward 2, Washington, District of Columbia, 20001, United States
Job Description
About the Team
Join the DataAnnotation team and contribute to developing cutting-edge AI systems. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.
As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here. Some team members fit this work alongside a full-time role, while others treat it as their primary focus.
Hiring Process
To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.
Location and Eligibility
This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand.
Work location
Work model: Remote
880 P, 880, P Street Northwest, Shaw, Logan Circle/Shaw, Ward 2, Washington, District of Columbia, 20001, United States
Washington, District of Columbia
Key Responsibilities
- check_circleDesign and solve quantitative problems to train and benchmark AI systems
- check_circleProvide feedback to shape next generation of AI models
- check_circleWrite clear technical explanations and well-documented analytical code
- check_circleEvaluate AI-generated quantitative work for technical accuracy and validity
Requirements
- verified2+ years of hands-on experience in a quantitative role or research environment
- verifiedCoding experience required
- verifiedPractical experience with statistical methods, predictive modeling, and experiment design
- verifiedFluency in English (native or bilingual level)
- verifiedBachelor's degree in a quantitative field preferred
- verifiedAvailable in US, Canada, UK, Ireland, Australia, and New Zealand
Benefits & Perks
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Skills, education and keywords
Skills: data science, statistics, economics, finance, physics, biology, epidemiology, operations research, statistical analysis, predictive modeling.
Education: Bachelor's degree in a quantitative field preferred quantitative field.