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Salary
$58k – $144k per year (Estimated)
Location
In office
Overview
Company
Impact
Profile match
Headquartered in London, United Kingdom, Quartz (Quartz Digital Ltd) is an AI-powered personal wealth management fintech provider. The company offers a digital platform that acts as an automated personal banker, combining Open Banking infrastructure with artificial intelligence to aggregate multi-bank accounts, analyze individual financial portfolios, and deliver real-time wealth guidance.

Summary

As an Engagement BI Analyst within the Insights and Data Group team, you will support the delivery of insight and analysis into CRM, marketing, customer, and campaign performance across our digital brands. You will use data to help stakeholders understand business performance, identify trends, and make informed decisions that support CRM and marketing objectives.

You will work with campaign, customer, and marketing data to produce reports, dashboards, and deep-dive analysis. Using appropriate analytical and statistical methods, you will help measure performance across key areas such as conversion, reactivation, retention, cross-sell, customer behaviour, and campaign effectiveness.

The role requires strong analytical thinking, attention to detail, and the ability to communicate findings clearly to both technical and non-technical audiences. You will be expected to turn analysis into concise conclusions, recommendations, and visualisations that are easy for stakeholders to understand and use.

You will work collaboratively with colleagues in Business Intelligence, Marketing, and other business areas to understand requirements, apply agreed analytics standards, and ensure outputs are accurate, well-managed, and aligned with data governance guidelines. You will also actively seek feedback and use it to improve the quality, relevance, and impact of your analytical work.

Key responsibilities include:

  • Analyse CRM, campaign, customer, and marketing performance data to identify trends, explain changes in business performance, and support data-led decision-making.

  • Produce regular reports, dashboards, and deep-dive analyses that provide clear, accurate, and actionable insight into campaign performance and business impact.

  • Track and report on key performance indicators, including conversion, reactivation, retention, cross-sell, campaign ROI, and other relevant CRM and marketing metrics.

  • Leverage advanced statistical methods and machine learning algorithms for exploratory and deep-dive analysis, optimization and segmentation models.

  • Communicate analytical findings, including relevant statistical or mathematical concepts, to non-technical audiences at an appropriate level of detail.

  • Develop clear data narratives and visualisations that help stakeholders understand performance, customer behaviour, and opportunities for improvement.

  • Ensure analytical work is produced, managed, documented, and shared securely in line with data governance, quality, and analytics guidelines.

  • Use established coding practices and standard tools, including SQL, Python, Tableau, or similar technologies, to solve business problems and deliver analytical outputs.

  • Support the development of analytical solutions that follow expected standards for data quality, reconciliation, monitoring, data modelling, storage, and security.

  • Work with Marketing and BI stakeholders to understand business context, clarify requirements, and ensure analytical outputs are relevant to the intended audience.

  • Consolidate analysis into concise conclusions and recommendations, supported by quality data and clear evidence.

  • Actively seek feedback and review from colleagues and stakeholders, using this input to improve the quality and usefulness of analytical outputs.

  • Support analysis of audience behaviour, segmentation, targeting, customer journeys, and campaign effectiveness to help improve marketing performance.

  • Monitor relevant industry trends, CRM practices, and platform changes, sharing observations where they may affect reporting, analysis, or campaign performance.

Requirements

You will need to have:

  • Experience in an analyst role, ideally within CRM analytics, marketing analytics, customer analytics, digital analytics, or business intelligence.

  • A solid analytical mindset, with the ability to use data to investigate business questions, identify trends, and support practical recommendations.

  • A good understanding of the mathematical and statistical concepts relevant to analytics, such as probability, sample sizing, extrapolation, interpretation, and performance measurement.

  • Experience analysing campaign, customer, CRM, or marketing performance data.

  • Ability to create clear reports, dashboards, and visualisations that explain analysis in a way that is appropriate for the audience.

  • Working knowledge of SQL and at least one BI or visualisation tool, such as Tableau, Power BI, Looker, or similar.

  • Some experience with Python, R, or another analytical programming language would be beneficial, particularly for analysis, automation, or data preparation.

  • Understanding of data quality, reconciliation, documentation, secure data handling, and analytics governance principles.

  • Ability to work with some ambiguity, ask clear questions, and structure analysis in a logical way.

  • Good written and verbal communication skills, including the ability to explain technical or analytical concepts to non-technical stakeholders.

  • Ability to build effective working relationships with stakeholders and understand the business context behind analytical requests.

  • A collaborative approach, with willingness to seek feedback, learn from others, and contribute positively to the wider BI team.

  • A degree in Business Analytics, Mathematics, Statistics, Computer Science, Technology, Economics, or equivalent practical experience.

Desired

Preferred Experience and Skills:

  • Experience working with CRM tools, marketing platforms, campaign management systems, or customer data platforms.

  • Experience analysing customer lifecycle performance, including conversion, retention, reactivation, segmentation, targeting, or cross-sell activity.

  • Familiarity with campaign measurement approaches, including control groups, test-and-learn methods, uplift analysis, or ROI measurement.

  • Experience developing dashboards or deep-dive analysis using predefined standards and templates.

  • Thorough understanding of descriptive and inferential Statistics.

  • Experience using Python, R, or similar tools for data manipulation, automation, statistical analysis, or repeatable reporting.

  • Understanding of BI and data warehousing concepts, including data models, data pipelines, DWH loads, and data storage principles.

  • Experience working in an online, digital, e-commerce, gaming, media, or other customer-led business environment.

  • Interest in marketing, CRM, customer behaviour, and the commercial drivers of the business area being supported.

The above list of duties is not exclusive or exhaustive and the post holder will be required to undertake tasks that are reasonably expected within the scope and grading of the post.

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