Developing innovative geospatial datasets to enhance estimates of regional economic activity and trends;
Undertaking robust and rigorous analysis in the delivery of consultancy projects including applying quantitative analytical techniques to large datasets using a variety of tools;
Building solutions to support clients make better-informed decisions using different forecasting methods, statistical models, and GIS solutions;
Taking the lead on aspects of project work, managing them from inception to completion addressing challenges along the way, including managing whole projects with the support of a project director;
Working with senior colleagues to develop research proposals, innovative methodologies, and developing proposals to meet client requirements,
Taking the initiative in suggesting ways to strengthen the quality of our analysis, including exploring new areas of application, with progression to proactively developing new business opportunities.
Communicating with clients and potential clients effectively, responding promptly and positively to their inquiries, with progression to leading on existing and potential client relationships;
Being able to plan and structure your own workload, balancing priorities across projects and other responsibilities with line manager support, with the potential for progression to line management responsibilities; and,
Supporting the continued development of the team, sharing knowledge and expertise, and mentoring junior colleagues, and bringing new ideas and techniques to the team.
Requirements & Skills:
Strong academic education in economics, geography, computer science, or related discipline;
Excellent analytical and quantitative skills;
Experience in using database programming languages using software such as R, Python, Stata, QGIS, or EViews;
Experience with geospatial-specific statistical modelling, such as geographically weighted regression, spatial autoregressive modelling, as well as traditional econometric models;
Experience with leveraging machine learning techniques for both classification and regression outputs;
Experience in analysing and modelling large geospatial datasets using GIS and/or statistical modelling software; and,
Strong written and verbal communication, including the ability to explain technical concepts and quantitative results to non-specialists.
Experience with climate variables and/or climate modelling is desirable but not required.
