[Remote] Analytics Engineer - AI Trainer
Note: The job is a remote job and is open to candidates in USA. DataAnnotation is seeking experienced quantitative professionals to contribute to developing cutting-edge AI systems. 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)
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.
Company Overview