Wholesale Trade Specialist

About the role

This role sources independent specialists to build evaluation frameworks and training data for AI systems in wholesale trade and B2B distribution. Specialists design prompts and rubrics that assess AI performance against real-world logistics and procurement scenarios.

Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.

Key facts

What you'll do

Each prompt targets realistic outputs that align with actual distribution and procurement workflows.

Rubrics remove subjective interpretation so scores remain reliable across repeated assessments.

This data trains and validates models on realistic wholesale and logistics workflows.

Fact-checking protects the quality and realism of every benchmark task.

Requirements

The posting states a pay range of $10 to $30.

Demonstrated professional expertise within wholesale trade, B2B sales, procurement, or distribution management is required to craft realistic evaluation scenarios. This expertise ensures scenarios match industry practices and standards.

Deep knowledge of industry standards, wholesale terminology, and supply chain logistics is applied when designing tasks and assessment criteria.

Strong writing and prompt generation skills are used to develop highly realistic, complex B2B task scenarios for AI evaluation. These skills produce engaging and challenging prompts for models.

Objective rubrics are created with little room for subjective interpretation to support reliable, repeatable scoring. Clear criteria enable consistent evaluation by any qualified scorer.

A , detail-oriented approach verifies supplier catalogs, pricing tiers, distribution contracts, and inventory information. This diligence ensures benchmark data reflects real-world constraints and expectations.

Work is conducted autonomously to produce high-quality evaluation frameworks and structured training data. Contractors manage their own workflows while delivering structured outputs.

Nice to have

Contractors bring demonstrable professional expertise from wholesale trade, B2B sales, procurement, or distribution management backgrounds. This experience informs realistic scenario design.

Experience writing evaluation rubrics and generating prompts for AI systems is preferred. Such experience helps create clear assessments and effective AI task prompts.

Skills & tools

Familiarity with B2B distribution workflows and inventory management concepts is essential. Understanding these workflows supports accurate scenario and rubric design.

Tools commonly used include AI prompt interfaces and document collaboration platforms. These tools enable efficient prompt development and rubric documentation.

Practical notes

Contractors must supply a secure computer and high-speed internet connection. Reliable hardware and connectivity are required for autonomous work.

Company-sponsored benefits such as health insurance and paid time off do not apply for this engagement. Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Tasks in this role involve evaluating AI outputs against professional wholesale and logistics standards. The work relies on clear rubrics and fact-checking to ensure data quality for model training. Specialists operate remotely and manage their own schedules within the defined deliverables. Common tools include AI prompt interfaces and document collaboration platforms. The role requires familiarity with B2B distribution workflows and inventory management concepts.