At a Glance
- Tasks: Support the consulting team with spatial data analysis and visualisation for impactful projects.
- Company: Join a specialist technology consultancy with a focus on innovation and collaboration.
- Benefits: Enjoy hybrid working, skill development, and the chance to work on diverse projects.
- Other info: Work in a dynamic environment with opportunities for growth and learning.
- Why this job: Kickstart your career in GIS while making a real difference in data-driven solutions.
- Qualifications: Degree in GIS or related field; some experience in spatial data analysis preferred.
The predicted salary is between 25650 - 31350 £ per year.
An opportunity exists for a Junior GIS/Data Consultant to join a specialist technology consultancy, working across a varied portfolio of spatial data and consulting projects. The role would suit someone in the early stages of their career with a strong grounding in GIS and spatial data who wants to develop broader experience across spatial analysis, data management, automation and consulting.
Selection of responsibilities:
- Supporting the consulting team to deliver data-driven outputs across a range of projects and sectors
- Undertaking spatial data analysis and visualisation to provide meaningful insight
- Using FME and other data integration tools to transform, validate and manage spatial and non-spatial data
- Working with senior consultants to design and implement automated workflows that improve the efficiency and reliability of data processes
- Supporting requirements gathering, data analysis and solution design
- Contributing to client meetings, workshops and technical demonstrations
- Supporting technical queries and sharing knowledge across the team
- Developing your skills across GIS, data integration and automation technologies
Selection of skills:
- A degree in GIS, Spatial Data Science or a related discipline
- Demonstrable experience applying spatial data analysis and visualisation, ideally with 1-2 years' GIS/data experience or relevant practical experience gained through an industry placement year
- Current technical knowledge of advanced spatial analysis techniques and their application to deliver insight
- Experience with proprietary and/or open-source GIS technologies
- A good understanding of data management, transformation and manipulation
- Strong communication, organisation and problem-solving skills
- A proactive approach and willingness to learn and develop
- Experience with some of the following would be useful, but isn't essential:
You'll work alongside experienced consultants while developing your technical and client-facing skills across GIS, FME, data integration and consulting. The role offers hybrid working, with 2-3 days per week onsite in Central Birmingham, alongside occasional UK travel associated with client projects.
Right to work: Applicants must have an unrestricted and ongoing right to work in the UK. We are unable to offer visa sponsorship for this role, either now or in the future. Please only apply if you will not require employer sponsorship to continue working in the UK.
Junior Data Consultant (GIS) in Birmingham employer: MSA Data Analytics Ltd
Join a leading financial services organisation that prioritises employee development and fosters a collaborative work culture. As a Finance Analyst in this role, you will benefit from comprehensive training opportunities, a supportive team environment, and the chance to engage with various stakeholders, all while contributing to meaningful regulatory reporting initiatives. Located in a vibrant area, the company also offers competitive benefits and a commitment to work-life balance, making it an excellent choice for those seeking a rewarding career in finance.
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We think you need these skills to ace Junior Data Consultant (GIS) in Birmingham
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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