Correlation One is seeking a motivated and experienced Teaching Assistant for Data Analytics to support learners in a fully virtual learning environment. This role is ideal for data professionals who are passionate about education and enjoy helping others build confidence in analytics skills.
In this position, you will assist in delivering structured data analytics programmes, supporting learners who are new to the subject and guiding them through key concepts. You will play an important role in ensuring a smooth and engaging learning experience for participants, including Amazon learners, as part of a large-scale training initiative.
The ideal candidate will have a strong background in data analytics, along with excellent leadership, communication, collaboration, and organisational skills. You should demonstrate empathy, patience, and flexibility when working with diverse learners, as well as a genuine passion for teaching and knowledge sharing.
Experience working in a fully virtual environment is essential, along with excellent written and spoken English. Strong interpersonal skills and the ability to support learners effectively in an online setting are key to success in this role.
A live onboarding session will be provided, during which you will be introduced to programme structures, platforms, and expectations. Full training materials will be made available before, during, and after onboarding to ensure you are fully prepared for the role.
Apply today to join Correlation One as a Teaching Assistant in Data Analytics and contribute to shaping the next generation of data professionals.
Position: Teaching Assistant – Data Analytics
Job Type: Full Time
Salary: £13.01
Location: Remote
Job description:
Correlation One is the largest provider of AI and data workforce development programs globally, having trained over 500,000 professionals across 11 countries. As the largest training provider for Amazon Career Choice, and a growing partner to state governments building registered apprenticeship programs, Correlation One sits at the intersection of employer talent needs and scalable workforce training.
We work with Fortune 500 enterprises, federal and state government agencies, and leading employers to close skills gaps in AI, data analytics, cybersecurity, and operations leadership. Our programs produce job-ready graduates who are prepared to contribute from day one.
Program Details
The Data Analytics program will run from Monday, June 15, 2026 to Wednesday, November 18, 2026. Live lectures will take place Mondays and Wednesdays from 5PM – 7PM GMT/6PM – 8PM CET. *Daylight Savings Time might affect these hours
A day in the life
Onboarding (Pre-Program):
We will host a live onboarding session, where we will walk through the program elements, set you up on our platforms, and ensure that you are prepared to support our Amazon learners effectively before the program launches.
All training materials will be provided in advance of, during, and after onboarding sessions.
Key Responsibilities:
Expectations during live (synchronous) sessions:
- Attend and proactively engage in the mandatory Pre-Program TA Onboarding. Dates and times will be announced.
- Monitor appropriate Pumble channels (#c1-TA, #live-chat, #extra-help, and other relevant channels) for learner questions and answer them promptly.
- Check-in with learners after each live session by asking how they’re feeling about the content, if they have any questions, or if there is anything that they need further clarity.
- Facilitate breakout rooms during lecture time, when applicable.
- Assist in keeping the session progressing should the Lead Instructor experience technical difficulty or is otherwise unable to deliver the lecture.
- If assigned to cover a specific live lecture, be present throughout the lecture and address learner concerns.
Expectations during days of no live sessions:
- Monitor appropriate Pumble channels for learner questions and answer them within 24 hours.
- Foster discussion by posing questions of your own and sharing relevant links in the #resources channel or in other appropriate Pumble channels.
- Use the #c1-TA channel to share any important information during a lecture that needs the attention of Correlation One staff or fellow Expert Network staff.
- Review content materials (including lab, projects, extended cases, etc..) for the next lecture to ensure you are prepared to answer Learner questions.
- Hold up to six (6) Individual Office Hours per week with learners in the program so they can ask any additional questions or get support as necessary.
- Grade Learner submissions of exercises and projects within seven (7) days of submission.
- Video walkthroughs for asynchronous assignments, such as extended cases and portfolio tasks.
- Support continuous program improvement by providing thoughtful feedback to Correlation One team via Weekly Write Ups.
- Submit weekly write-ups summarizing the week’s accomplishments and challenges and provide insights on each learner. In addition to potential improvements.
- Attend and participate in the weekly staff meeting with Correlation One team and other Expert Network staff.
- Attend all scheduled meetings with your camera on, ensuring active engagement and professional presence.
Who you are
- Data Analytics professional with exceptional leadership, communication, collaboration, and organizational skills.
- Empathy, flexibility, patience; passion for working with diverse learners who are new to data analytics content.
- Experience operating in a fully virtual environment.
- Excellent written and spoken English language skills.
Working experience with the following technical skills/platforms:
- Microsoft Excel
- Tableau
- SQL
- Python
- Zoom
- Pumble
- Prior teaching experience with adult learners is a plus
Compensation
The compensation for this position is specific to location and takes into account the wide range of factors that are considered in making compensation decisions. These factors include (but are not limited to) location, experience, education and skill sets.
Application Process
Application Deadline
Open until filled