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Data Analyst

Job in Manchester, Greater Manchester, M9, England, UK
Listing for: Interactive Investor
Full Time position
Listed on 2026-01-14
Job specializations:
  • IT/Tech
    Data Analyst, Business Systems/ Tech Analyst, Data Science Manager, Data Engineer
Job Description & How to Apply Below

WHO WE ARE:

interactive investor is an award-winning investment platform that puts its customers in control of their financial future.

We’ve been helping investors for over 25 years. We’ve seen market highs and lows and been resilient throughout. We’re now the UK’s number one flat-fee investment platform, with assets under administration approaching £70 billion and over 500,000 customers.

For a simple, flat monthly fee we provide a secure home for your pensions, ISAs, and investments. We offer a wide choice of over 40,000 UK and international investment options, including shares, funds, trusts, and ETFs.

We also bring impartial, expert content from our award-winning financial journalists, highly engaged community of investors, and daily newsletters and insights.

PURPOSE OF ROLE:

As a Data Analyst in the Data and Innovation team at interactive investor, you will be a key driver of the organisation’s data-centric culture, harnessing data to inform strategic business decisions. Your role is to synthesise complex data sets into clear, actionable insights that shape product optimisation, customer engagement, and operational efficiency.

Reporting to the Data Analytics and Insights Manager, you will take a lead in data storytelling, influencing the direction of products and services by understanding customer behaviours and market trends.

You will foster a collaborative environment where knowledge sharing and continuous improvement are paramount. Your expertise will contribute to the development of a centralised data analytics framework, bridging the gap between technical data analysis and strategic business initiatives.

You will be responsible for maintaining and advancing our data reporting systems, ensuring they provide a robust foundation for data-driven decision-making across the company. At times you may need to make predictive models to be able to understand the potential impact that changes may have against our business.

In this role, you will be expected to stay abreast of the latest tools and techniques in data analytics, bringing innovative solutions to the table and maintaining the team’s competitive edge – for example in tools like: SQL, Snowflake, Python, Google Analytics/other web analytics, Power BI.

Your contributions will directly impact interactive investor’s ability to deliver enhanced customer experiences, optimise products and services, and drive business growth.

Through your work, you will help establish a legacy of data excellence within the organisation, positioning interactive investor at the forefront of investment platforms that leverage data for success.

KEY RESPONSIBILITIES:
  • Analyse Data and Generate Insights
    :
    Extract and analyse data from our data lakes and relevant sources to provide actionable insights for business decisions and strategy formulation
  • Reporting and Visualisation
    :
    Develop, maintain, and automate insightful BI and MI reports, ensuring data accuracy and relevance. Champion the automation of reporting capabilities to enhance efficiency
  • Reporting Automation: Work to automate reporting capability through effective use of SQL, Python, Power BI, and other tools to streamline the data analysis process
  • Collaborative Analysis: Develop strong partnerships with stakeholders from Product, Commercial, Technology, Customer Services, and Operations, etc., to understand requirements, to support their data needs and encourage the leveraging of data for product and service improvements, and create a data-led culture
  • KPI and Data Insight Development: Lead or contribute to the development and tracking of KPIs and data insights across the company, ensuring a consistent set of measures is used for decision-making.
  • Analytics Platforms: Utilise platforms such as SQL, Snowflake, Power BI, Usabilla, Google Analytics, Optimizely, Content Square, and Hotjar for in-depth analysis and to create insightful reports
  • Data Science Techniques
    :
    Apply data science methodologies, for example, statistical modeling, segmentation analysis, time series analysis, and some predictive techniques to analyse customer behaviour patterns and assess business impacts, collaborating with Data and Innovation team members…
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