Specialist Technician (Learning and Teaching): Analytics and Forecasting

THIS JOB HAS NOW CLOSED

The opportunity

This is an exciting opportunity for an Analytics and Forecasting software specialist to join a leading college in fashion education and play a key role providing technical assistance to students and staff to support the day-to-day operation of our excellent teaching and learning facilities.    

You will be working predominantly from home supporting students online and working with the course leader and academic team for the MSc Fashion Analytics & Forecasting course. This MSc is currently the first Master’s programme in the world to apply data analytics and forecasting in the context of fashion business.    

Reporting to the Technical Coordinator, you will be part of a specialist technical team responsible for delivering technical workshops and software support to students and staff online and in-person.   

You will provide professional expertise, guidance and advice to students and staff working with analytics and forecasting software and contribute to the delivery of academic activities within the College. Such tools currently include Qualtrics, R Studio, IBM SPSS Statistics, Microsoft’s SQL Server, Microsoft Power BI, and Adobe In-Design.  The list is regularly reviewed with industry partners to ensure currency.   

In addition, you will also provide support for student learning through informal and formal training and instruction. A key part of the role will be to contribute critical input to student concept and expressive/creative intention, including giving feedback to students and contributing to student formative assessments.   

The start date for this position is 01 August 2023 onwards.

About you

You will need a high level of multi-platform, multi device digital literacy, with demonstrable contemporary and forward-thinking expertise in data visualisation, machine learning, time series analysis and forecasting, quantitative methods, and statistical data analysis.   

You will also need experience of delivering technical workshops and providing 1-2-1 support for analytics and forecasting software issues as well as experience of working in experience of working in data visualisation and machine learning. 

We are UAL

University of the Arts London (UAL) generates and inspires the creativity the world needs for a better future. Since 1842, our colleges have been defining creative education. With curiosity, imagination and intent we make work which creates lasting change for people and our planet. London is core to who we are, a place where we meet and share ideas with people from different backgrounds and cultures.

Our creative network influences learning, culture, industry and society on a global scale. Our academics and practitioners deliver creative education and inspire new ways of thinking through research and innovation. We work with students at every level from pre-degree and short courses to postgraduate and online learning, enabling them to build the careers they want. Together, we are a community of makers, thinkers, pioneers and storytellers redesigning the future.

Our culture

We are a global University, welcoming over 22,000 students and 6,000 staff from 130 countries. We aim to be a university where people can be themselves and feel supported to reach their full potential. That’s why we are proud to be members of the Race Equality Charter (REC) and Business Disability Forum, are a Disability Confident Scheme Committed and Living Wage employer and maintain our status as a Stonewall Diversity Champion.

Application process

We operate a fair and open anonymous selection process. Thus, you will need to create an account and submit an application through our job board. As part of this, you will need to provide a supporting statement/answer some competency questions to demonstrate your suitability. Our recruitment process involves: Application, Shortlisting, Interview and Assessment, Offer, Onboarding.

We understand the benefits of using AI in work. But, if you are thinking of using it to submit an application, we ask you to think about what value it adds. AI tools tend to lack the personal touch and authenticity we value in candidates. We encourage you to showcase your unique knowledge and skills using your own voice.

If we receive a high volume of applications, the closing day date might close early. We aim to communicate any changes to the closing date with at least 24 hours’ notice. If you have any general questions or have accessibility needs, please refer to our Contact us page.

Find out more about London College of Fashion

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