Product Operations Manager Full Time

Business Operations / Product Operations Manager — UK Insurance

Role purpose

UK Insurance is scaling a portfolio of recurring, monthly-cadence data products,. These products now represent a material share of ARR, margin contribution and growth, but the operating model supporting them has not yet been industrialised to match their commercial importance.

Today, a significant amount of recurring operational work is distributed across analysts as a secondary responsibility. That model has worked historically, but it now creates avoidable friction: fragmented ownership, inconsistent execution, context switching, limited workflow visibility, variable QA, and too much reliance on tacit knowledge.

This role exists to create a central point of operational ownership for the lower-touch product portfolio. The objective is to make recurring delivery visible, controlled, repeatable and scalable, while preparing the business for Jira-based workflow management, greater automation, AI-enabled operational support, and future platform migration.

The role reports to the Head of Insurance and sits at the intersection of client operations, workflow management, operational control, product operations and business process improvement.

Core Objective:

• To centralise and improve the operational management of UK Insurance’s lower-touch product portfolio, reducing fragmentation across the team, improving visibility and control, and building a more scalable, automation-ready operating model.
• The successful candidate will help move the business from a model dependent on individual analyst effort and informal coordination towards a more governed operating model with clear ownership, documented processes, visible workflows, standard controls and better management information.

Strategic context

UK Insurance is moving towards a more productised, platform-enabled operating model. That means recurring products need to be run with clearer process ownership, better workflow discipline, stronger operational data, and more consistent handoffs between commercial, analytical, product and technical teams.

• This role will support that transition by:
• creating operational visibility across monthly product workflows;
• reducing the burden of recurring coordination work on analysts;
• improving quality control and escalation routes;
• standardising processes, templates and documentation;
• supporting migration from informal tracking into Jira-based workflow management;
• improving BI and management reporting on workload, capacity and cost-to-serve;
• identifying opportunities for automation and AI-enabled operational support;
• preparing workflows for future data platform migration and more scalable delivery.
• This is not a purely administrative role. It is an operational leverage role: making the existing business easier to run, easier to measure, and easier to scale. Glamorous, obviously.

Key responsibilities

1. Workflow ownership, operational control and first-line QA

• Own the recurring operational workflows across the low-touch product portfolio, from data ingestion through to client output delivery.
• Responsibilities include:
• maintaining visibility of workflow status, deadlines, dependencies and blockers;
• coordinating handoffs between analysts, client-facing teams and other internal stakeholders;
• ensuring routine work is completed in a timely, consistent and controlled way;
• carrying out first-line QA on standard client data inputs, workflow steps and outputs;
• identifying anomalies, missing inputs, process failures or delivery risks early;
• escalating substantive analytical, client, data or technical issues to the appropriate owner;
• ensuring that delivery routines are followed consistently across products and clients.
• The role does not replace analytical ownership. It ensures the recurring operational machine is properly run, observed and controlled.

2. Process standardisation, documentation and scale readiness

• Document and improve the processes that support the monthly cadence product portfolio.
• Responsibilities include:
• mapping existing workflows, dependencies, controls and failure points;
• producing clear standard operating procedures, checklists and process diagrams;
• identifying unnecessary manual effort, duplication, rework and avoidable dependencies;
• introducing standard templates for recurring delivery, escalation and QA;
• helping define appropriate ownership rules across operational, analytical and commercial teams;
• supporting the migration of workflow management into Jira;
• ensuring that process design supports future automation and platform migration;
• maintaining process documentation so that knowledge is not locked inside individual analysts’ heads.
• The emphasis is on making the business more robust and scalable before major technology change, rather than waiting for a platform migration to magically fix operational disorder. It will not.

3. Jira workflow management and operational tooling

• Help design and maintain a Jira-based workflow management model for recurring product operations.
• Responsibilities include:
• translating recurring product workflows into practical Jira stages, statuses and ownership rules;
• maintaining boards, tickets, templates and workflow conventions;
• creating simple reporting views for progress, bottlenecks, workload and delivery risk;
• supporting adoption of Jira across the team in a pragmatic, low-friction way;
• using Atlassian tooling, including Rovo where appropriate, to improve workflow discovery, documentation and knowledge retrieval;
• ensuring operational tooling supports the way the business actually works, rather than becoming process theatre.
• This role should help create the bridge from today’s spreadsheet-led operational tracking towards a more transparent and durable workflow management model.

4. Management information, BI and operational reporting

• Improve the quality of operational information available to the Head of Insurance and wider leadership team.
• Responsibilities include:
• supporting monthly vertical reviews and quarterly business updates;
• maintaining operational inputs into BI-driven management reporting;
• improving visibility of workload, service performance, capacity, time tracking and cost-to-serve;
• supporting evidence-based decisions on resourcing, automation and investment;
• helping reconcile operational activity with product portfolio value and commercial priorities;
• highlighting trends in workload, bottlenecks, failure points and delivery efficiency.
• The role should help the business understand not only what work is being done, but what it costs, where it creates risk, and where improvements would create the greatest leverage.

5. Automation and AI-enabled operational improvement

• Identify and support practical opportunities to reduce manual effort and improve operating leverage through automation and AI-enabled tools.
• Responsibilities include:
• identifying repeatable workflow steps suitable for automation;
• supporting use of AI tools for documentation, workflow summarisation, process mapping and knowledge management;
• helping structure operational information so that future AI tools can work from trusted, well-organised sources;
• supporting controlled experimentation with tools such as Claude, Rovo and other approved enterprise AI systems;
• ensuring AI use is grounded in business process improvement rather than novelty;
• working with technical and product stakeholders to prepare processes for future platform migration.
• The role does not require deep software engineering expertise. It does require enough operational curiosity and technical confidence to spot where manual work can be reduced, structured or improved.

Tools and systems

The candidate is expected to work with, or quickly become comfortable with:

• Jira for workflow management, operational tracking and delivery visibility;
• Confluence / documentation tools for process maps, SOPs and operating playbooks;
• Atlassian Rovo where useful for knowledge discovery, workflow support and documentation;
• Power BI / Excel for operational reporting, workload tracking and management information;
• Salesforce as a source of commercial and client context;
• approved enterprise AI tools, including Claude, for documentation, summarisation and operational support;
• future platform and data workflow tooling as the business prepares for migration to a more scalable data environment.

Prior experience with all of these tools is not essential. The important requirement is fluency in structured operating models, comfort with systems, and the ability to turn messy recurring work into visible, repeatable process.