PM/SPM B2B Student crowd
Product Manager – Data & Intelligence
Product Manager – Data & Intelligence
Reports to: Director of Product Team: Product, alongside two other Product Managers Salary: £55,000–£65,000
The role
We have a lot of data, a lot of ideas and no shortage of interesting problems to solve.
What we don't want is a Product Manager who simply takes those ideas, turns them into tickets and keeps Jira tidy.
We're looking for someone who gets curious about the problem first.
You'll help us understand what our customers across the living sector are really trying to do, turn assumptions into hypotheses, find the evidence that matters and decide what is genuinely worth solving.
Then you'll work closely with Engineering, Data and the rest of StudentCrowd to figure out the right solution and get it into customers' hands at the right time.
You'll own a product area within our Data & Intelligence portfolio, working with the Director of Product on direction and priorities while having plenty of freedom over how you get there.
We believe strongly in freedom and responsibility. You'll have space to make decisions, challenge assumptions and try things. In return, we expect you to own the outcome, not just the output.
What you'll actually do
Find the right problems
● Talk to customers. Look at the data. Spend time with Commercial and Customer Success. Understand what is happening rather than immediately jumping to what we should build.
● Turn problems and assumptions into clear, testable hypotheses. Know what evidence would make you change your mind.
● Sometimes the loudest request will be the right thing to do. Sometimes it won't be. Part of your job is knowing the difference.
Decide what deserves our time
● There will always be more opportunities than Engineering capacity. ● You'll prioritise using customer evidence, product data, commercial impact and effort
rather than who asked most recently or shouted loudest.
● You'll own the backlog and roadmap for your area, but we care much more about the quality of the thinking behind them than how beautiful the Jira board looks.
Build with people, not for them
● Engineering and Data aren't teams we hand requirements to. ● You'll bring them into problems early, explore possible solutions together and make
sensible trade-offs between value, complexity, speed and quality. ● You'll work particularly closely with our Data Operations and Data Engineering teams
because much of what makes our products valuable starts with trusted, useful data.
Get things into the real world
● Discovery is useful only if it eventually leads somewhere. ● You'll turn validated problems into clear outcomes and requirements, work with
Engineering through delivery, make decisions when things get messy and help get products into customers' hands.
● Then you'll find out whether they actually worked. Launch isn't the finish line.
How we work
We try to be hungry, humble and smart.
● Curious: Go looking for the real problem. Ask good questions, talk to customers, explore the data and resist jumping straight to a solution.
● Grounded: Let evidence beat opinion. Stay close to customers and outcomes, know what you know and what you don't, and be willing to change your mind when the evidence changes.
● Bold: challenge assumptions and groupthink respectfully. Make decisions, take ownership and be prepared to say “we shouldn't build this” when that's the right call.
We want a healthy challenge. If everyone agrees immediately, we'd quite like you to ask what we might be missing.
And because we give people freedom, we expect responsibility. Own your decisions. Communicate them clearly. Measure what happens. Learn and adjust.
You'll probably be good at this if...
● You already have experience working as a Product Manager and have shipped real products with Engineering teams.
● You can take a loosely defined customer or business need and turn it into a properly understood problem rather than jumping straight to a feature or solution.
● You're comfortable talking to customers and asking questions that uncover what they actually need rather than simply collecting feature requests.
● You use qualitative and quantitative evidence to make decisions. ● You can work with engineers, data specialists, commercial teams and customers
without needing everyone to speak "Product".
● You're comfortable saying "I don't think we should build that yet" and explaining why.
● And you're interested in how AI is changing the way product teams work. We use AI heavily and expect our ways of working to keep evolving rather than treating today's PM processes as sacred.
It would be useful, but isn't essential, if...
● You've worked with B2B SaaS, data products, analytics or intelligence platforms. ● You understand enough about APIs, data pipelines and data quality to have
productive conversations with technical teams. ● You've worked in PropTech, property, higher education or another data-rich industry. ● But domain knowledge can be learned. Product judgement, curiosity and the
willingness to challenge your own assumptions matter more.
What good looks like
★ After your first year, we should be able to point to problems you helped us understand better, things we deliberately chose not to build because the evidence wasn't there, and products that customers are genuinely using because we solved something that mattered.
★ Engineering and Data should see you as someone who brings them good problems rather than predetermined solutions.
★ Commercial and Customer Success should trust that you understand their customers, even when you don't automatically say yes to every request.
★ And you should be able to show, with evidence, how the products you've helped build have made StudentCrowd's Data & Intelligence proposition better.
Where this can take you
● We're building the Product function as the company grows, so this isn't a role with a predetermined box around it.
● Do well and your scope grows with you: bigger problems, broader product areas and greater ownership, with a path towards Senior Product Manager and Lead Product Manager.
● We don’t expect you to arrive knowing everything.
We do expect you to stay curious enough to find the real problem, grounded enough to let evidence change your mind, and bold enough to challenge the room when something doesn’t add up.
Interview Process
Interview Process : 3 stages
1. Curious Conversation | 30 mins
A conversation about a product they’ve actually worked on. We’ll dig into the problem, how they knew it mattered, what they learned from customers and data, what assumptions changed, and what they chose not to build.
This is mainly about understanding how they really think about a product rather than walking through their CV.
2. Product Jam | 60 mins
This is the most important stage.
No case study, homework or presentation. We’ll put a realistic but deliberately ambiguous problem on the table and work through it together with the candidate, a PM and an Engineer.
We’ll give them information as the conversation develops and see what they ask for, how they frame the problem, form hypotheses, use evidence, collaborate and adapt their thinking.
There doesn’t need to be a polished solution at the end. Thinking is what matters.
3. Meet the Crowd | 45 mins
A more relaxed session with a few of the people they’ll work with across Engineering, Data and Commercial/CS.
This is about mutual fit and seeing how they communicate, disagree, make trade-offs and operate with freedom and responsibility.
Across all three, I’d like us to look for three behaviours: Curious, Grounded and Bold.
Curious enough to find the real problem. Grounded enough to let evidence change their mind. Bold enough to challenge assumptions and groupthink when needed.
- Product Manager – Data & Intelligence
- Product Manager – Data & Intelligence
- The role
- What you'll actually do
- Find the right problems
- Decide what deserves our time
- Build with people, not for them
- Get things into the real world
- How we work
- You'll probably be good at this if...
- It would be useful, but isn't essential, if...
- What good looks like
- Where this can take you
- Interview Process