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Product & data at Pet Media Group

We look after buyer and breeder journeys, own the data infrastructure behind group decisions and make sure every team can move fast with reliable information.

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Nathan, Chief Product Officer at Pet Media Group

Team led by

Nathan · Chief Product Officer

“We keep the loop short: talk to users, decide, build, measure. You will never wait months to see your work go live.”

Joined in 2022

Before PMG

Bumble logoSkype logo

Responsibilities

What the work covers

The day-to-day areas this team owns across our marketplaces.

Define buyer and breeder journeys and roadmap priorities

Build data pipelines, warehouse models and self-serve analytics

Run experiments, A/B tests and measure outcomes by market

Design products that balance growth with trust and safety

Deliver dashboards and insights that power group decisions

Maintain data quality, tooling and AI/ML support

How the team works

  • Every change starts with a problem and a measure, tested in one market before rollout.
  • Product, design, engineering, and data work as one team.
  • We own the data infrastructure end to end, from pipelines to self-serve analytics.
  • Safety and welfare trade-offs are part of every decision, not a final review step.

Tech stack

The tools and platforms the team uses to ship work, make decisions, and collaborate.

  • Amplitude
  • BigQuery
  • Claude
  • Elevenlabs
  • Figma
  • Jira
  • Looker
  • n8n
  • Notion
  • Survicate

In their words

Voices from Product & data

People in the team on what the work is actually like.

“I help the team draft, research, code, and summarise, so people can spend their time on judgement, relationships, and care instead. The point is not the novelty of it. It is that we get far more done for pets and families with a small team.”

Laika

PMG AI Agent

Location

Joined

2024

Before PMG

NVIDIA logo
“PMG is fully digital, so every search, message, and match leaves a trace we can learn from. The fun part is turning all of that data into something product teams can ship quickly, then watching it change real behaviour within days.”

Abdullah

Head of Data

Location

Joined

2024

Before PMG

Bolt logo
“If you are curious and you actually want to build things, there is no ceiling here. I have jumped between products, markets, and messy problems, and the constant is that people cheer you on for growing. That is rarer than it sounds.”

Daria

Senior Product Manager

Location

Joined

2022

Before PMG

Not listed

Open roles

Open roles in Product & data

Candidate questions

Questions about joining Product & data

The things candidates ask us most often, answered honestly before you apply.

General PMG questions

Four steps: an intro call with the recruiter, a conversation with the hiring manager, a practical exercise based on real work rather than puzzles, and a final conversation with two people you would work with day to day. Most candidates go from first call to decision in around three weeks, and we tell you where you stand after every step.

We read every application ourselves and aim to reply within five working days, whether the answer is yes or no. If a role is paused or already at offer stage, we tell you rather than leaving the application open.

We work hybrid around our offices in Stockholm and Berlin, and several roles are fully remote within compatible time zones. The job advert states the setup for each role, and we agree the pattern with you before you sign rather than after.

No. Most people join from marketplaces, classifieds, e-commerce or consumer platforms. What matters is that you care about the families, breeders and animals on the other side of the screen, and that you can work in a group where decisions move quickly.

Week one is onboarding, meeting the people you work with and getting to know the marketplaces. From there you take on something small and own it with support. By the end of the first month you are running your own piece of work with support from your manager and a buddy.

You have a weekly one to one with your manager, a lightweight check in each quarter against clear goals, and a fuller review twice a year. Progression is based on the scope you handle and the outcomes you drive, not on time served.

AI is part of the normal toolkit rather than a side project. It supports research, drafting, analysis and routine operational tasks, with a person reviewing anything that affects a family, a breeder or an animal. We expect people to be curious about better tools and to share what works.

Salary bands are set per market and shared during the first call, so nobody negotiates in the dark. Everyone gets a learning budget, generous holiday, home working support, and the equipment they want to do the job well.

People who take ownership without waiting for permission, who prefer shipping and learning to long planning cycles, and who are comfortable saying when something is not working. We are a group, not a corporation, and the pace reflects that.

Yes, and many people do. Treat the requirements as a description of the work rather than a checklist. If you can show how you would handle the core of the role, we would rather have the conversation than miss you.

Product & data-specific questions

Product managers, analysts and engineers decide together, using marketplace data and direct user conversations. Trade offs are written down so the reasoning survives longer than the meeting.

Event data from every marketplace flows into a shared warehouse with modelled tables and self serve dashboards. Analysts spend their time on questions rather than plumbing.

Yes. You define the hypothesis, work with engineering on the implementation, and read the results yourself. Experiments run continuously across markets so learning compounds.

You split time between understanding user problems, defining scope with design and engineering, reviewing metrics, and talking to marketplaces. No two weeks are identical, but each ends with something shipped or learned.

We score opportunities by user impact, business value and how much of the work carries across markets. A change that helps every market usually wins over a local optimisation, unless a market has a critical trust or safety need.

Research is continuous, not a phase. Product managers run interviews, surveys, and shadow sessions, and analysts validate patterns in behavioural data. Insights are shared openly so the whole group learns.

As one team. Product brings the problem, data brings evidence, and engineering brings feasibility. We write briefs together and review progress daily, so surprises are rare and small.

By outcomes, not output. We track usage, trust signals, conversion and retention against a clear baseline. If a feature does not move the metric, we learn fast and iterate or remove it.

Anything touching safety, payments or verification goes past Trust & Safety before launch, and rolls out market by market. Speed applies to learning, not to shortcuts around the people using the marketplaces.

Other teams

Have a look at our other teams

Every team works the same way: build systems rather than one-offs, measure what changes, and keep AI in the daily loop. Each team page covers the work, how the team runs and the roles open right now.

Engineering

Small engineering teams shipping to nine brands

See what the team does

Trust & safety

The team that defines what a safe marketplace looks like

See what the team does

Strategy & operations

From acquisition to marketplaces that run themselves

See what the team does

Marketing

Growth engineering that scales across nine brands

See what the team does

Breeder relations

Building long-term relationships with trusted breeders

See what the team does

Finance

The financial backbone of every marketplace decision

See what the team does