Geophysicist - AI Trainer

Join the DataAnnotation team to help develop cutting-edge artificial intelligence systems. This role offers the flexibility of remote work and the ability to set your own schedule. We are seeking experienced quantitative professionals to assist in advancing AI development. While AI models are becoming increasingly capable of complex analytical and scientific reasoning, they still require practitioners with real-world quantitative experience to validate whether their outputs hold up in practice. As a member of our team, you will collaborate closely with state-of-the-art AI models on tasks such as evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly influences how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or another quantitative field, if you think rigorously about data and models, your skills are applicable. Some team members perform this work alongside a full-time role, while others treat it as their primary focus. This position is available exclusively to residents of the US, Canada, UK, Ireland, Australia, and New Zealand.

Benefits

• Fully Remote: Work from anywhere within the US, Canada, UK, Ireland, Australia, and New Zealand.

• Flexible Schedule: Choose which projects to take on and determine when you work.

• Competitive Pay: Projects are compensated hourly, with rates up to $60 USD per hour.

• Impact: Help shape the future of AI systems designed to reason about data and analytics.

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, covering areas such as 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.

Qualifications

• Experience: 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 an adjacent field.

• Coding Skills: Some coding experience is required, with comfort in writing and reviewing analytical code end-to-end.

• Statistical Knowledge: Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time-series forecasting).

• Language Proficiency: Fluency in English (native or bilingual level) with strong writing skills.

• Education: 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.

• Credentials: Relevant credentials are a plus, such as Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise.