Coding / Data Analytics / SQL Tutor (Variable Hours)
| Dyddiad hysbysebu: | 12 Mawrth 2026 |
|---|---|
| Cyflog: | £29.71 yr awr |
| Gwybodaeth ychwanegol am y cyflog: | Including holiday pay |
| Oriau: | Rhan Amser |
| Dyddiad cau: | 19 Mawrth 2026 |
| Lleoliad: | Richmond, Surrey |
| Gweithio o bell: | Ar y safle yn unig |
| Cwmni: | Richmond and Hillcroft Adult Community College |
| Math o swydd: | Parhaol |
| Cyfeirnod swydd: | RHACC055-26 |
Crynodeb
About the Role
Richmond Business School is expanding its Digital and Creative Industries provision and has opened a new, purpose-built digital and creative suites to support learners who want to enter the creative sector, upskill for employment, or develop their freelance/business portfolio.
We are now recruiting variable hours (hourly-paid) Tutors with current industry expertise in coding/AI development/ Data analytics with familiarity with some or all of the following topics:
Python (Intro): setup, data types, variables, built-in functions/methods, functions, conditionals, simple program
Experience teaching data analysis / data science using Python (pandas, basic stats, model concepts) or applied ML awareness
Technical competence in Python-based neural network training and evaluation—including train/validation/test splitting, loss/accuracy metrics, gradient descent, hyperparameter tuning, inference, and PyTorch workflows such as using pre-trained models, GPU training scripts, image preprocessing, normalisation, data augmentation, batched data loaders, and saving/loading model checkpoints.
Teach SQL for data querying and analysis, using real-world datasets and decision-making scenarios.
Richmond Business School is expanding its Digital and Creative Industries provision and has opened a new, purpose-built digital and creative suites to support learners who want to enter the creative sector, upskill for employment, or develop their freelance/business portfolio.
We are now recruiting variable hours (hourly-paid) Tutors with current industry expertise in coding/AI development/ Data analytics with familiarity with some or all of the following topics:
Python (Intro): setup, data types, variables, built-in functions/methods, functions, conditionals, simple program
Experience teaching data analysis / data science using Python (pandas, basic stats, model concepts) or applied ML awareness
Technical competence in Python-based neural network training and evaluation—including train/validation/test splitting, loss/accuracy metrics, gradient descent, hyperparameter tuning, inference, and PyTorch workflows such as using pre-trained models, GPU training scripts, image preprocessing, normalisation, data augmentation, batched data loaders, and saving/loading model checkpoints.
Teach SQL for data querying and analysis, using real-world datasets and decision-making scenarios.