Data Science and Environmental Intelligence MSc

A skills gap is opening-up for both data science and environmental roles. GovUK (2021) estimates there are between 178k and 234k data science roles that need to be filled, with a lack of data scientists to fill them. This shortage is in the broader context that the data science industry is rapidly growing, with reasonable estimates for growth in the data economy in Europe ranging from 20% to 52% (Statista, 2020) and expectations that the data economy could make up 4.25% of EU and UK GDP by 2025. At the same time a drive for two million ‘green’ jobs by 2030, and a focus on a green industrial revolution, indicates an increasing market for environmental jobs as the decade progresses.<br/><br/>This MSc in Data Science and Environmental Intelligence is a faculty-wide MSc which is led by the Schools of Geography, Earth and Environmental Sciences (SoGEES). SoGEES will work alongside the School of Biological and Marine Sciences (SoBMS), and the School of Computing, Engineering and Mathematics (SECaM) to deliver a PGT programme designed to provide conversion training into an area that a) shows clear growth potential because of a skills gap in the labour market and b) is fully aligned with NERC’s recently published digital strategy. In so doing they will use existing SECaM (in Data Science) and SoGEES / SoBMS (research project) modules, and provide three new modules in marine and terrestrial sensing technologies and their applications as part of this programme.<br/><br/>This programme provides: <br/>• Hands-on, experiential learning <br/>• Industry-focused content that is rooted in the modern world <br/>• Teaching led by academics actively driving change <br/>• A sustainability-based education that empowers students to make a difference. <br/><br/>The new programme complements the existing PGT portfolio of all three Schools, building on existing expertise to tap into an emerging and rapidly evolving market. The specific focus on environmental intelligence – sensing, monitoring and management through the use of automation, AI and big data – will ensure that students are prepared to enter the jobs market and fill the skills gap that is predicted to emerge in the near future.