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Insight & Analytics Consultant

Job in Brighton, BN2, England, UK
Listing for: Graduate Recruitment Bureau
Full Time position
Listed on 2026-01-09
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, Data Science Manager, Data Engineer
Job Description & How to Apply Below
Location: Brighton

One of the largest providers of consulting and technology services, providing a collaborative, friendly and entrepreneurial environment. A truly global consultancy with offices based in central London and a broad client base of blue‑chip companies, the company operates across a variety of sectors and industries.

Working within their data science and analytics team, you will provide expertise and structured thinking, allowing you to develop innovative analytical solutions to complex business problems.

Role

Here you will sit within an industry‑leading Data and AI Advisory team, where you'll collaborate with clients to improve their use of data, becoming more data‑driven.

This role will give you the opportunity to work across diverse areas of tech and data including generative AI, user‑centred design, machine learning, data visualisation, data modelling and wrangling, as well as analytics governance.

  • You will help clients develop data products and models, roll out analytical tools, and scale their data capabilities.
  • You will create and design data and intelligence products with stakeholders to convert analysis into insight, which addresses the data needs of senior leaders and has a direct impact on service delivery and consumers.
The Individual

For your application to be successful, you will be required to have:

  • Previous experience on visualisation projects, creating end to end data models, from initial reporting requirements and business rules gathering to implementation
  • Creating dashboards and interactive visual reports using BI tools such as Power BI, Tableau, Qlik or Looker
  • Strong knowledge of querying and manipulating data using SQL, R or Python
  • Ability to translate complex statistical concepts and machine learning models to non‑technical stakeholders using visualisations
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