Insight Analyst - Roadside - NonVolume

🔒 Confidential Employer
Posted 22 March 2026
LOCATION
Home office
TYPE
Full-time
LEVEL
Mid-Senior level
SALARY
£60,000 / year
CATEGORY
Data Analysis
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

SQL Python R Data Analysis Basic Modelling Techniques Communication Skills

FULL DESCRIPTION

The Insight Analyst plays a key role in delivering high-quality analysis and insight to support decision-making across the AA. This is a hands-on role focused on data exploration, reporting, and analytical delivery. You will work closely with senior analysts, principal analysts, business partners and stakeholders to understand business questions and deliver actionable insights. You will be supported by senior team members and have a clear development path to grow your technical and business skills.

What will I be doing?

  • Deliver hands-on analysis using SQL and Python/R to support business decisions, including basic modelling and statistical techniques.
  • Work with senior analysts to translate business questions into analytical tasks.
  • Apply basic modelling techniques to support analytical tasks and generate predictive insights.
  • Support the development of insight-led data products in collaboration with data scientists and BI developers.
  • Collaborate with data engineering to ensure data quality and availability.
  • Document analytical processes and share knowledge with the wider team.
  • Participate in exploratory analysis to identify trends, patterns, and opportunities.
  • Receive mentoring and coaching from senior analysts to support your development.
  • Contribute to a culture of continuous improvement and analytical excellence.

What do I need?

Capability, Knowledge and Experience:

  • Experience in data analysis using SQL and Python or R.
  • Ability to work with large datasets and apply analytical techniques.
  • Familiarity with basic modelling approaches such as regression, clustering, or classification.
  • Strong attention to detail and a passion for data.
  • Good communication skills and ability to explain findings clearly.
  • Willingness to learn and take on new challenges.
  • Familiarity with agile ways of working is a plus.

Education and Qualifications:

  • University degree in a quantitative field preferred.
  • Relevant certifications in analytics or data science tools are an advantage.

Personal Characteristics:

  • Curious and eager to learn.
  • Collaborative and team oriented.
  • Organised and able to manage time effectively.
  • Proactive and enthusiastic about using data to solve problems.
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