About the role
✨ DataForce by TransPerfect is looking for middle and high school educators (teaching students aged 11–18) to participate in our project, Cadence! ✨
Work Location: Remote in Germany
Engagement Model: Freelance; Independent Contractor
Estimated Workload: ~5.5 hours (3 rounds of 1.5-2h each); starting the week of October 19th, until end of November.
Tasks
What is the project about?
The purpose of this project is to evaluate educational content specifically designed for middle and high school students. This assessment will be used to optimize the overall performance of a multilingual learning application.
Requirements
Who is eligible?
To participate, you should meet the following qualifying criteria:
Be a resident of Germany;
Be a native-level speaker of German;
Be proficient in English, as all communication and task guidelines will be in English;
Be qualified as a middle or high school educator for students aged 11–18;
Have experience in teaching whole classes;
Preferred: At least 3 years of experience teaching text-intensive subjects at the middle or high school (students aged 11–18).
Benefits
How much is the compensation?
Compensation is task-based, with expected compensation up to an hourly rate of $ 45 USD on average, provided productivity and quality expectations are met.
Training (1h duration estimated) will be paid at the hourly rate above upon successful completion.
As payment methods we offer PayPal, Gift Card and Wire Transfer, according to your location and preference.
🙌 Interested? Apply now!
Please feel free to share this opportunity with teachers in your network, so they can join the project and make a meaningful difference!
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DataForce by TransPerfect is part of the TransPerfect family of companies, the world’s largest provider of language and technology solutions for global business, with offices in more than 100 cities worldwide.
We offer high-quality data for Human-Machine Interaction to some of the most prestigious technology companies in the world. Our department focuses on gathering, enriching and processing data for Machine Learning in different AI domains.
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