Public Company Investor Relations Expert

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help experienced professionals find focused, short-term projects, consolidate proof of work, and grow a durable freelance portfolio in the human side of AI.

OpenTrain is the hiring and contracting organization for this role. You will join a community of contributors who shape how AI systems behave by producing high-quality training deliverables and evaluations.

About AI training and why it matters

AI training (data labeling / human feedback) is how modern models learn from real-world examples and expert judgment. Skilled contributors prepare, evaluate, and rank content that teaches AI to write, reason, and communicate accurately.

This role applies investor-relations expertise to document-based evaluation tasks: producing professional deliverables that teach AI how to understand public-company communications and capital-markets reasoning.

The role

You will complete self-contained exercises using mock results packs, shareholder registers, and analyst models, then produce polished deliverables that are graded against a rubric. Work is contractor, part-time (less than 20 hours/week), remote, and paid hourly at $85–$100 USD.

Deliverables include earnings releases, prepared remarks, Q&A briefings, guidance recommendations, investor-day decks, ownership analyses, activist-vulnerability assessments, and dividend/capital-return recommendations.

• Schedule: Less than 20 hours per week; flexible, work-from-anywhere.
• Pay: Hourly, USD $85–$100/hour.
• Language: English required; role is open worldwide.

What you'll do

• Draft earnings releases, prepared remarks, and Q&A briefings for quarterly results calls.
• Produce guidance-setting and revision recommendations with supporting scenarios.
• Build investor-day materials, equity-story and positioning decks, AGM materials, and deal announcement packages.
• Analyze shareholder registers and ownership bases to assess activist vulnerability.
• Prepare dividend and capital-return recommendations and outline strategic options.
• Work from mock results packs and analyst models, then submit graded deliverables per a rubric.

Requirements

• 4+ years in an in‑house investor relations role at a public company (required).
• Direct ownership of an earnings cycle, including release, script, Q&A, and analyst engagement.
• Familiarity with investor-day and earnings-call deliverables for public companies.
• Proven ability drafting earnings releases, prepared remarks, and Q&A briefings.
• Experience building investor-day materials, equity-story decks, and AGM packages.
• Experience analyzing shareholder registers, ownership bases, and assessing activist vulnerability.
• NIRI IRC charter is a plus; sell-side equity research or IR-agency experience is a plus.

Who should apply

This role is aimed at seasoned IR professionals who want flexible, freelance work that leverages their public-company experience. Ideal applicants have run earnings cycles, engaged analysts, and prepared strategic communications and capital-return recommendations.

If you enjoy producing polished written deliverables, working from mock packs and models, and getting fast, rubric-based feedback, this role fits well with part-time consulting or portfolio freelance work.

• You must be comfortable working independently on document-based exercises and meeting quality rubrics.
• Open to contractors worldwide who can work in English and accept hourly contractor pay.

How it works

Apply through your OpenTrain profile. If selected, you'll receive structured exercises with mock materials and a clear rubric. Complete tasks on a flexible schedule, upload deliverables, and receive feedback and payment per hours worked.

OpenTrain centralizes your proof of work so you can show credible experience for future AI-training projects and build a long-term freelance portfolio in the AI training industry.

• Employment type: Contractor, Part-time.
• Data type: Document evaluation and rating tasks; label type: evaluation_rating.
• Compensation is hourly and paid in USD at the stated range.