Compare the Market

Events

• Set the strategic direction for events at CtM, covering both business and fun activities
• Lead and manage the end-to-end organisation and delivery of all Compare the Markets’ events including large scale annual offsite
• Accountable for overall Events budget, including budget management of each event, ensuring we are cost-effective
• Responsible for stakeholder management across the business (including Exec and extended leadership team)
• Manage and own all relevant supplier and partner contracts, sourcing vendors and suppliers, negotiate costs, SLAs and T&Cs maintaining strong diligence throughout
• Identify and implement mechanism/s to measure the success of every event, for reporting upwards to key stakeholders. Make sound recommendations for change and development of future events
• Lead across the matrix to gain relevant support for the successful delivery of events, for example engaging the internal communications team on content aligned to strategy and the marketing team for brand purposes
• Understand and interpret the company strategy and make recommendations for events and activities which will help embed knowledge and understanding across the business
• Establish oneself as CtM's events expert, supporting and advising local teams on smaller team events
• Maintain excellent customer service of all events showcasing high performance and brilliant delivery
• Use external insight of trends and developments in events management, ensuring CtM remains best in class for colleague events to ensure you proactively seek new ideas and make recommendations​

Events Manager

Operations

• Own the operating model, proactive preventative governance, and intake and prioritisation of work into the AI capability layer.
• Support strategic planning, maintain the opportunity backlog co-owned with Product, and ensure planning decisions translate into sequenced, investable execution.
• Act as the principal resource for forming high-profile new initiatives alongside Exec.
• Shape the delivery function for a world where 10x systems are built by agents, ensuring frameworks, governance, and performance measures keep pace.
• Manage structured triage and prioritisation processes across Technology, Data, AI and Commercial domains.
• Provide senior stakeholders with visibility of priorities, pipeline health, delivery progress, and strategic dependencies.
• Lead quarterly planning and investment processes, translating strategic priorities into realistic, investable plans.

Senior Delivery Operations Manager

Program Manager

• The Programme Manager is responsible for leading and delivering change programmes across the Enterprise Services portfolio
• Embedded within the HRIS team and reporting to the Head of Enterprise Services
• Partnering with the HRIS Service Delivery Manager to plan, govern and execute end-to-end change across HRIS, SaaS solutions, Microsoft 365, end user compute and networking
• Translating strategic priorities and Oracle releases into deliverable plans
• Managing RAID, budget and programme governance
• Co-ordinating internal teams and external implementation partners
• Reporting progress, risks and benefits to SteerCos and Tech leadership
• Managing Enterprise Services programme budgets, forecasts and benefits cases
• Responsible for managing change delivery through internal teams and external implementation partners
• Maintaining a structured RAID for Enterprise Services programmes

Programme Manager – Enterprise Services

Manager

• Own planning, prioritisation, and sequencing across the Data & AI team.
• Apply a deep understanding of data work, skills, and technical dependencies to shape realistic delivery plans and roadmaps.
• Support senior decision-making by clearly articulating options, trade-offs, and delivery implications.
• Stay close to delivery to identify risks, dependencies, and opportunities early.
• Challenge and support teams on scope, sequencing, and approaches to solving delivery problems.
• Use delivery insight to improve focus, flow, and outcomes across teams.
• Define and use delivery metrics to track progress, predictability, and outcomes across the portfolio.
• Ensure appropriate governance, transparency, and documentation of delivery decisions to meet audit and compliance expectations.
• Act as a trusted delivery partner to Data & AI leaders and business stakeholders.

Data Delivery Manager

• Accountable for end-to-end delivery performance at the Mission level, ensuring outcomes are achieved to agreed timelines, quality standards and strategic priorities.
• Drive operational discipline by embedding delivery metrics into decision-making and ensuring clear visibility of progress, risk and value delivered.
• Lead Agile ceremonies (stand-ups, sprint planning, retrospectives, and stakeholder reviews).
• Identify, resolve and prevent delivery blockers and optimise workflows to accelerate delivery speed and reduce waste working in collaboration with Portfolio Managers.
• Champion delivery excellence through consistent performance monitoring, root cause analysis and implementation of improvements.
• Ensure cross-team coordination, managing dependencies with Product and Engineering teams.
• Own dependency management and proactively manage risks, escalating when necessary to ensure delivery is not impacted.
• Work with Engineering Managers and Product Managers to resolve technical and business dependencies.
• Ensure realistic scoping of work, avoiding overcommitment while maintaining delivery momentum.
• Act as the accountable owner for delivery outcomes, dependency management, risks and data-driven reporting. Align with Product Managers to prioritise effectively and enable informed decision-making.
• Partner closely with Delivery Enablement, Engineering Managers, and Product Leaders to ensure Mission delivery directly contributes to pillar-level strategy and organisational objectives, driving both short-term wins and long-term capability uplift.
• Champion and scale Agile ways of working, embedding practices that increase adaptability, collaboration, and speed to value. Use delivery performance metrics (e.g., predictability, cycle time, throughput) to inform strategy, identify improvement opportunities, and track measurable gains in delivery efficiency and quality.
• Lead high-impact retrospectives and performance reviews that result in clear, measurable improvement actions.

Technology Delivery Manager

Data Scientist

• Lead your team in building predictive systems that run continuously
• Design and oversee automated workflows
• Shape how your team approaches AI-powered systems
• Ensure every model connects to a real outcome
• Set the standard for modelling quality
• Take ownership of model performance in production
• Be hands-on in design sessions
• Guide your team through fast-moving tooling landscape
• Champion responsible, auditable AI
• Encourage and model the use of AI-assisted development tools
• Work closely with commercial, product, and engineering leads
• Develop your data scientists through regular feedback
• Contribute to hiring

Data Science Manager

Product Analyst

• Analyse customer behaviour and product performance
• Support Product Managers in understanding customer journeys, user engagement, conversion, and retention
• Conduct exploratory analysis to answer product and business questions
• Define and measure product success metrics and KPIs
• Design, execute, and analyse A/B tests and product experiments
• Build and maintain dashboards and reporting solutions
• Partner with Analytics Engineering teams to ensure KPI definitions, business logic, and product instrumentation are accurate
• Apply AI and machine learning techniques to enhance product understanding and measurement
• Collaborate closely with Product Managers, Designers, Engineers, and Data teams

DevOps Engineer

• Design, configure, and operate highly available database and data storage systems
• Drive reliability, performance, scalability, and operational excellence across database environments
• Lead platform improvement initiatives
• Monitor, optimise, and automate database operations
• Identify and address technical debt and performance bottlenecks
• Support reliability of data pipelines and services
• Participate in incident response and continuous improvement activities
• Collaborate with engineers and data specialists

Database Site Reliability Engineer

• Contribute to the development of machine learning solutions from design through to deployment
• Build and evaluate predictive models using Python and SQL
• Translate business challenges into structured data science problems
• Conduct statistical analysis and feature engineering to generate actionable insights
• Support A/B test design, evaluation, and interpretation with rigour and clarity
• Collaborate with stakeholders to ensure data science solutions are well aligned to product and business needs
• Work with ML Engineers to support deployment, monitoring, and performance tracking of your models
• Contribute to team standards on reproducibility, documentation, and model evaluation
• Apply responsible AI practices to ensure fairness and transparency
• Take part in peer reviews, knowledge sharing, and internal learning sessions
• Support and coach junior team members and peers, contributing to their growth
• Play an active role in shaping our data science culture and community