Healthcare Admin, Legal, Engineering and Finance Professionals: Scenario Building for AI Environments

What We're Researching

We're running a paid study on how work in healthcare administration, legal, finance, and engineering can be accurately modeled inside reinforcement learning environments. By building realistic scenarios from these fields, we can better train artificial intelligence systems to handle complex decision-making. Your expertise will directly inform the structure and logic of these simulated worlds.

Time Expectations

10 hours / week.

How It Works

During this remote session, you will interact with our reinforcement learning platform built for these fields. You will be asked to map out common scenarios from your field, detailing the variables, constraints, and potential outcomes. The platform will guide you through building these simulated worlds while you explain your reasoning. You will also provide feedback on how accurate and easy to use the modeling tools are.

Who This Is For

We are looking for experienced healthcare administration, legal, finance, and engineering professionals who know the day-to-day work in their field well. We welcome certified financial analysts, quantitative analysts, and corporate finance managers, as well as revenue cycle and patient access managers, practising attorneys, and industrial, civil, mechanical and electrical engineers. A technical background or prior experience with AI platforms is helpful but not required.

Responsibilities

• Interact with a reinforcement learning platform built for these fields
• Map out realistic scenarios from your field using platform tools
• Define the variables, constraints, and logic behind real scenarios in your field
• Provide feedback on the accuracy and usability of the scenario builder

Requirements

• Active professional in healthcare administration, legal, engineering, or finance and accounting
• Solid understanding of how decisions get made in your field
• Comfortable using new technical platforms and modeling tools
• Able to clearly explain the principles and constraints of your field