Senior Product Manager

The Marketing Meetup Ltd; Dundee; On-site; GBP 65,000 - 80,000; Full time

Benefits offered by this job

Bonus and equity

Pension: 5% matched company pension

34 days holiday leave

Job summary

Broker Insights is hiring a Senior Product Manager to own problem areas across broker and insurer sides of the platform and drive sprint work toward long-term strategy and P&L growth. You will define direction, sequence sprints, and be accountable for commercial outcomes, not just releases.

The role requires data-driven problem framing, collaboration with data science and engineering on AI capabilities, strong stakeholder management, and the ability to work remotely or from our Dundee hybrid

Qualifications

• 5+ years in product management, including 2+ years at senior level owning strategy and roadmap for a significant area.
• Deep experience managing data products, with a strong background in AI, machine learning and analytics.
• Track record of shipping B2B SaaS features adopted by customers, with measurable results.
• Analytical skills with data-driven, hypothesis-driven decision making.
• Experience across several product areas and adaptability in unfamiliar domains.
• Excellent data literacy and ability to work with data engineers/scientists.
• Strong stakeholder management and ability to align diverse teams.
• Disciplined in scoping and delivering iteratively.
• Excellent written communication and ability to produce clear specs.
• Comfort operating with ambiguity and with senior stakeholders.
• Commercial insurance, broking, MGA, insurtech or regulated data-heavy market experience.
• Experience with data quality, entity matching, or data enrichment.
• Experience taking AI or ML capabilities from concept to trusted product.
• Familiarity with UK financial services regulation.
• Experience in scale-up environments building processes.

Responsibilities

• Define strategy and roadmap for assigned problem areas and end-to-end sprints.
• Own sprint sequencing and accountability for commercial results.
• Translate customer and market insights into problems statements.
• Collaborate with data science and engineering to apply AI/ML where appropriate.
• Ensure output is explainable and trusted by users.
• Work with sales, customer success, and marketing on release and rollout.
• Mentor other product managers and raise craft quality.
• Represent product in exec discussions with clear, evidence-based views.

Skills

Product management

Data products

AI & ML awareness

Stakeholder management

Commercial awareness

Job description

Broker Insights | Fully remote or hybrid (Dundee) | £72,500 P.A. | Full-time, permanent

Commercial insurance does not need more data. It needs more insight.

ABOUT BROKER INSIGHTS

Broker Insights is a leading provider of data analytics and market insight for the global commercial insurance industry. Our award-winning platform, Broker Insights VISION™, compiles and standardises commercial insurance market data, enabling brokers and insurers to develop a new way of working together.

We launched in the US in 2023 with an offering tailored to that market. In 2026 we launched a totally re-engineered tech stack and AI Search, which will become the search engine of commercial insurance.

VISION already powers over 40% of the UK market's placement decisions. We are ISO 27001 certified and ICO registered. Broker Insights Ltd is authorised and regulated by the Financial Conduct Authority.

We are growing fast. This role will suit someone ambitious who takes the initiative and makes themselves a key member of the team.

THE ROLE

We are hiring a Senior Product Manager to own sets of problem areas and the sprints that resolve them, and to drive those areas towards long-term strategy and P&L growth.

You are not being handed a market or a product line to administer. You are being handed the problems that matter most and the mandate to solve them properly. For each area you own, you set the direction, sequence the sprints that get you there, and stay accountable for the commercial result — not just the release.

Your problem areas will span both the broker and the insurer side of the platform, and they will change as the business does. What stays constant is the standard: every sprint you run should be traceable to a strategic objective and to a number that matters.

Our users are broker principals, market placement teams, underwriters and insurer distribution leads. They are commercially sharp, time-poor, and they will tell you exactly when something does not work. Your decisions show up in user engagement and in real commercial outcomes for our brokers and insurers.

Reports to: Product Lead

WHAT YOU WILL OWN

The strategy and roadmap for your assigned problem areas — agreed with the Product Lead, Leadership and Exec teams, defended by you, and revisited as priorities shift. Within those areas you own the sprints end to end: what gets picked up, in what order, and what each one is expected to deliver.

You are accountable for the long‑term trajectory of those areas and their contribution to P&L growth, not simply for shipping the work. Problem areas are drawn from across broker and insurer products and the data foundations beneath them, so expect to get up to speed on an unfamiliar area quickly and to hand work back cleanly once it has landed.

WHAT YOU WILL DO

Strategy for your areas

• Identify high-impact opportunities through data analysis, market intelligence and customer insights.
• Own the strategy and roadmap for the problem areas assigned to you, and defend the trade-offs to the exec team, to customers and to your engineers.
• Set a multi-quarter view for each area — where it needs to get to, and the sequence of sprints that will take it there.
• Shape and evolve the plan honestly when priorities or evidence change, rather than defending a roadmap past its usefulness.
• Act as a thought leader in AI, machine learning, agentic systems and analytics trends, embedding this into product direction and helping the business understand where autonomous AI creates step-change value and where human oversight is essential.

Framing the problem, understanding the customer and market intelligence

• Act as the voice of the customer internally, using qualitative and quantitative research to uncover needs and pain points.
• Sharpen each problem before any solution is discussed. What is actually wrong, for whom, and what is it costing us?
• Size it with real numbers — market coverage, placement volume, retention risk, cost to serve — and push back when a problem does not stand up against the alternatives.
• Get in front of brokers and insurers regularly. Turn what you hear into evidenced problem statements, not feature requests.
• Work hypothesis-first. State what you expect to happen, validate it against data, and design the experiment that will prove or disprove it.

Running the sprints

• Work day to day with engineering, data science and commercial as a single team. Write clear specs, define acceptance criteria, and stay close through delivery.
• Partner with data science and engineering to spot where AI and machine learning genuinely improve the product, then design those capabilities so the output is explainable and trusted.
• Translate data collection and processing into visualisation and actionable insight — the value lands with the user, not in the pipeline.
• Apply a strong understanding of UX, scalability and platform performance considerations.
• Scope to what can ship inside the sprint. Cut early and cut visibly rather than letting a sprint run long.
• Hold a high bar on data quality and matching accuracy — in our market, a wrong match costs more than a missing feature.
• Move confidently between broker-side and insurer-side problems, and be honest about what you do not yet know about an unfamiliar area.

Landing the outcome

• Define the success metric before the sprint starts and report against it afterwards. Adoption, not delivery, is the finish line.
• Partner with sales, customer success and marketing on release: positioning, enablement, and a tiered rollout that suits the audience and the size of the change.
• Hand work back cleanly — documented, instrumented, and owned by someone — so nothing you touch becomes orphaned.
• Support key customer and insurer conversations where product credibility moves the deal.

Influence

• Set the standard for how product work is done here — discovery, written thinking, decision records, metrics.
• Mentor and support the other product managers in the team, and raise the quality of the craft across it.
• Manage stakeholders across data science, engineering, commercial and exec, and keep them aligned on what you are solving and why.
• Represent product in exec-level discussions with a clear, evidenced point of view.

WHAT YOU WILL BRING

• [5]+ years in product management, including [2]+ years at senior level owning strategy and roadmap for a significant area, with accountability for a commercial number.
• Deep experience managing data products, with a strong background in AI, machine learning and analytics.
• A track record of shipping B2B SaaS features that customers actually adopt — with numbers you can talk through.
• Proven analytical skills and demonstrable success with data-validated, hypothesis-driven, experiment-tested decisions.
• Evidence of working across several product areas rather than one, and getting productive in an unfamiliar domain quickly.
• Strong data literacy. You can interrogate a dataset, write or read a query, spot a suspect number, and work fluently with data engineers and data scientists.
• Excellent stakeholder management. You can hold a room of data scientists, engineers and commercial leads to a single agreed direction.
• Discipline with scope. You can take a vague problem, cut it to something shippable in a sprint, and say no to the rest.
• Excellent written communication. You think in documents, and your specs leave no room for interpretation.
• Comfort operating with ambiguity and with senior stakeholders who disagree with each other.
• A solutions-oriented approach, deep curiosity about customer needs, and a genuine growth mindset.
• Commercial insurance, broking, MGA or insurtech experience, or another regulated data-heavy market such as financial services or healthcare.
• Experience with data quality, entity matching, or data enrichment products.
• Experience of taking AI or machine learning capabilities from concept through to a product users trust.
• Familiarity with UK financial services regulation and its practical effect on product decisions.
• Experience of scale-up environments where the process is something you help build.

WHAT WE OFFER

• Bonus and equity: EMI Options Scheme available, and eligibility for the company bonus plan
• Pension: 5% matched company pension contributions
• Holiday: 34 days holiday leave, plus your birthday off
• Sick leave: 14 days company sick leave
• Parental leave: Up to 13 weeks at full pay
• Wellbeing: Holistic Employee Wellbeing Framework and a fully funded Employee Assistance Programme for you and your family
• Working pattern: Fully remote, or hybrid from our offices in the Waters' Edge building in Dundee, with some travel to team days, on‑sites and customer meetings

DIVERSITY AND INCLUSION AT BROKER INSIGHTS

We are passionate about diversity and believe our differences make us stronger as a team. Our inclusive culture is founded on a belief that our people will always be our biggest asset, and that a collaborative environment where everyone has a voice will always deliver the best results.

We welcome the unique contributions our employees bring. Different professional and social life experiences add to our collective knowledge and help drive innovation.

HIRING PROCESS

1. Introductory call with the Product Lead — 15 minutes

2. Product craft interview with the Product Lead — 60 minutes

3. Practical exercise and discussion with product, engineering and data — 30 minutes

4. Final conversation with Peter Scott, CEO — 30 minutes

BETTER DATA | BETTER INSIGHTS | BETTER BUSINESS