ABOUT NOUS
Nous is an AI agent that takes some of the load of life; making good decisions and acting for our users in areas where they're not the experts or aren't paying enough attention. We've started with optimising bills, where we're already saving households thousands, and are now expanding into new categories. Similar to how Amazon picked books as its first category and grew from there. We're growing fast, and it's working. 20x YoY growth makes us one of the fastest scaling startups in the UK. And NPS of +70 (higher than Apple) shows that our users love it. We've just launched two more novel new products (on top of our existing bill optimisation). Insurance: we're the first to get the regulatory approval and build the tech to actually do the full insurance discovery and purchase journey as an agent for the user (not just give them a link to the best deal). Subscription management: lots of companies use Open Banking to draw pretty graphs, we're the first to use it to actively save people money starting by cancelling unwanted subscriptions for them. It would be easy to look at this and think we've got it all figured out. But we've only scratched the surface; our ambitions are SO much higher. We're building a new category of product which is hard, so we've stacked the deck in our favour: an experienced founding team with multiple exits, and investors including the founders of Monzo, Wise, Booking.com, lastminute.com, Onfido, Funding Circle, Tide, Habito and more. Still, the problems we're solving are hard. 'Talk is cheap' applies to agents too. To have REAL impact, agents need to break out of the sandbox and take action in the real world where there are consequences. This means solving all the hard, thorny, interesting, frustrating problems the real world has to offer.
ABOUT THE ROLE
Across energy, mobile, broadband, insurance and subscriptions, Nous has grown 20x in the last 12 months. Our reporting hasn't always kept pace. We're hiring a Head of Business Intelligence to own this and fix it. That means you'll set the standards rather than inherit them. No legacy team, no committee, no five-year-old semantic layer you're not allowed to touch. Which cuts both ways. Take our unit economics. Revenue per household is a commercial assumption rather than a column in a table, and it varies as a function of behaviour, service lines managed, engagement. Some users are Premium, some not; some suppliers pay a bounty per switch, some pay nothing. Households change providers, cancel services, then switch again, and their value compounds over time in a complex way. Getting from a decent estimate to a genuinely defensible view of LTV, payback and cohort behaviour is one of the highest-leverage things anyone could do here, and it's the kind of problem that has no textbook answer. To get there you'll own the data foundations too: canonical definitions of our fundamental metrics, the dbt models underneath them, and the reporting that Growth, Commercial, Operations and Finance depend on. We've built quickly and there's real judgment and craft required to make that as solid as the business now requires but doing so in a scrappy and pragmatic way. You'd work directly with the senior team: CEO, Head of Finance, and the Growth, Commercial, Operations and Product leads. Your work is what the board sees. Our current stack is Postgres replicated into Snowflake via Fivetran, dbt for transformation, Omni for modelling and dashboards, Amplitude for product analytics, and Statsig for experimentation, plus a growing set of bespoke dashboarding and reporting instrumentation.
KEY RESPONSIBILITIES
Own the canonical definitions. Sponsor an agreed definition for each fundamental metric. Then hold the line intelligently when someone wants a subtly different version for their deck.Own the models underneath. Our dbt and Omni models have grown alongside the business, and there's a satisfying piece of work in consolidating them, moving everything onto our current event standard, and retiring what's no longer earning its place.Make the numbers provable. Events, database tables and the finance ledger should agree, and you'd build the reconciliation and automated checks that keep them agreeing as we scale.Make self‑serve work properly. A clean semantic layer, sensible naming, documentation people actually read, and a small set of dashboards trusted enough that nobody builds their own version on the side.Own commercial reporting and unit economics: revenue per switch by product and supplier, contribution margin, CAC and payback by channel, cohort retention, repeat switching, LTV. Partner with Finance on management reporting, the board pack, and the reporting infrastructure behind investor updates.Be the analytical partner to the commercial teams. Growth needs to know which channels work. Commercial needs to know which supplier deals are worth doing. Operations needs to know where the process leaks. Answer those questions, then build the reporting that stops them being asked again.Set the governance: access, PII handling, how deleted users are treated in analytics, what can and can't leave an aggregate. Plus the commercial side of the data stack itself, since pipeline spend at our scale is worth someone owning properly.Continue to drive the use of AI. Most of our analytical work now happens in Claude Code alongside SQL. We'd expect you to continue to push this hard.
ABOUT YOU
You're the person who noticed the number was wrong. Somewhere you've worked, there was a metric everybody quoted that didn't survive contact with the underlying data, and you were the one who found it, worked out why, and fixed it properly instead of adding a footnote. You'll likely thrive in this role if:You're commercially minded as well as technically strong. You can build the model, and you have a view on what it says. When you present a cohort curve you have an opinion about what we should do about it.You're fussy about correctness in a way other people find slightly excessive. You triangulate. You reconcile. You won't ship a chart you can't defend, and you're comfortable pushing back on a number senior people have grown attached to, because you've already checked it three ways.You've done this from scratch. You've walked into a fast‑growing company where the reporting was held together with string and made it solid. You know what order to do it in, and which bits can wait.You're hands‑on and expect to stay that way. You'll be writing the SQL and building the models yourself for a good while. We keep the middle thin on purpose.You simplify. Faced with forty dashboards, your instinct is to work out which six matter and kill the rest. You'd rather have a few things everyone trusts than a complete set nobody opens.You build with AI tools daily. Not "I've tried ChatGPT". You use Claude Code or similar as part of how you actually work: writing and debugging SQL, navigating an unfamiliar schema, automating your own checks.
ESSENTIAL EXPERIENCES
substantial experience in analytics, BI or data leadership, including a spell owning the numbers for a fast‑growing consumer or transactional business. We care more about what you've built than the years attached to it.Confident SQL. Handed
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Head of BI in London employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
