Remote AI Training & Analytics Engineer

DataAnnotation; Menlo Park (CA); On-site; USD 69,000 - 138,000; Full time

Benefits offered by this job

Fully remote

Flexible schedule

Competitive pay

Impactful work

Job summary

DataAnnotation seeks an Analytics Engineer - AI Trainer for a remote contract role. Based in Menlo Park, CA, you will help train AI models by assessing quantitative outputs, crafting tasks, and delivering feedback to improve AI systems designed for quantitative reasoning.

You will design and solve tasks across forecasting, experimental analysis, and statistical inference, write clear explanations, and maintain analytical code to support model improvements and benchmarks.

Qualifications

• 3+ years in a quantitative role or research environment (data science, statistics, economics, finance, physics, biology, epidemiology, operations research, etc.)
• Some coding experience; able to write and review analytical code end-to-end
• Experience with statistical methods, predictive modeling, and experiment design (A/B testing, hypothesis testing, regression, classification, time-series forecasting)
• Fluency in English with strong writing skills
• Bachelor’s in a quantitative field; advanced degree a plus; credentials (Kaggle, AWS/GCP ML certs) a plus

Responsibilities

• Assess AI-generated quantitative work across stats, modeling, and data insights for technical accuracy and practicality.
• Design quantitative tasks to train and benchmark AI, including forecasting, experimental analysis, optimization, and inference.
• Write clear technical explanations and maintain well-documented analytical code.
• Provide feedback to inform next-gen AI models focused on quantitative reasoning.

Skills

Statistical methods

Experiment design

Coding experience

English writing

Education

Bachelor's degree in quantitative field

Master’s or PhD (advantage)

Tools

Python

SQL

R

Job description

DataAnnotation seeks an Analytics Engineer - AI Trainer for a remote contract role. Based in Menlo Park, CA, you will help train AI models by assessing quantitative outputs, crafting tasks, and delivering feedback to improve AI systems designed for quantitative reasoning.

You will design and solve tasks across forecasting, experimental analysis, and statistical inference, write clear explanations, and maintain analytical code to support model improvements and benchmarks.