Senior Product Analyst – Spend

Zilch is a payment tech company on a mission to create the most empowering way to pay for anything, anywhere. Combining the best of debit, credit and savings, we give our customers the option to earn instant cashback or spread the cost of pricier purchases, completely interest free and with no late fees.

We started in 2018 with a small team and a big dream – to make credit accessible to all. Since then, we’ve achieved double unicorn status and taken on more than 5 million customers. There are some exciting projects coming up and we’ve got big growth plans.

Want to join us?

The Senior Product Analyst, Spend will be a strategic analytics partner to the Product Managers who own Zilch’s Spend domain – the infrastructure and systems that power every payment Zilch processes.

You’ will partner across product teams spanning Acquiring (payment routing, acceptance, acquirer integrations, wallet payments) and Spend Platform (billing, ledger, collections.  Together, these two teams own the infastructure that other teams depend on for how we bill and ultimately collect money from our customers as efficiently as we can.

Reporting to the Lead Product Analyst, you’ll join a team of two other analysts covering the Spend domain – but you’ll be the first Product Analyst based in our Krakow office. There’s fluidity in how the team covers the domain; you’ll be expected to range across teams and problems rather than sitting rigidly within one product squad.

This is not a reporting role. You’ll sit alongside PMs as their analytical counterpart – the person who spots what they can’t see in the data, challenges assumptions with evidence, and brings the insight that changes what gets built next. You’re at your best when you’re pulling at a thread no one asked you to pull at, and surfacing an opportunity or risk that reshapes a product decision.

The opportunity to make an impact here is immediate. This domain is deeply commercial and the levers are tangible: optimising billing strategy and collection rates, improving payment routing to lift authorisation rates, reducing cost-per-transaction through smarter acquirer selection. Basis points and percentage points compound into millions at Zilch’s volume – and many of the biggest wins are sitting in the data waiting for someone curious enough to find them.

Be the analytical partner to Product

• Work shoulder-to-shoulder with PMs as their thought partner – helping frame problems, pressure-test hypotheses, and make better decisions faster.
• Proactively investigate the “why” behind metric movements, customer behaviour shifts, and product performance – don’t wait to be asked.
• Bring insight to planning: identify the highest-value opportunities and risks in the data, and shape what the product teams prioritise next.
• Translate complex analysis into clear, opinionated recommendations – not just observations.

Follow your curiosity into the data

• Dig into transaction-level data to uncover patterns in spend behaviour – frequency, basket size, merchant category mix, payment method preference, repeat usage, and edge cases.
• Identify and size opportunities to grow GMV and improve unit economics before they appear on anyone’s roadmap.
• Quantify the revenue and margin impact of product changes (interchange optimisation, routing logic, decline recovery, retry strategies, billing improvements) – make the invisible visible.
• Explore ambiguous, ill-defined problems. The best insights in this domain won’t come from a well-scoped brief – they’ll come from you asking “what if?” and “why not?”

Design and run experiments

• Design and analyse A/B tests and quasi-experiments across payment routing, checkout flows, card provisioning, spend nudges, billing strategy, and acceptance optimisation.
• Establish incrementality and causal frameworks where randomisation isn’t feasible (e.g., scheme routing changes, issuer-level interventions).
• Partner with Engineering to ensure clean event instrumentation and experiment infrastructure for the Spend domain.

Collaborate across the data and product organisation

• Partner with Core Data and Engineering on data modelling, pipeline quality, and event tracking for the spend domain.
• Communicate findings clearly to Product, Engineering, Finance, and senior leadership – adjusting depth and framing for the audience.

Must have

• 4–6 years’ experience in product analytics, payments analytics, marketplace analytics, or a closely adjacent quantitative role.
• Genuine curiosity – you’re the person who notices something odd in a dataset and can’t let it go until you understand why. You generate insight, not just answer questions.
• Advanced SQL and strong data manipulation skills – you can independently explore large, messy transactional datasets, define the right cuts, and build robust analyses without hand-holding.
• Solid experimentation skills – you can design clean tests, reason about statistical power and validity, handle edge cases, and present results with appropriate caveats.
• Strong product instincts – you think in terms of customer behaviour and business outcomes, not just data tables. You can recommend what to build, not just measure what was built.
• Clear, confident communication – you can distil complex findings into crisp, opinionated narratives for product, commercial, and exec audiences.
• Comfort with ambiguity – you’ll be building analytical foundations in an evolving domain. You’re energised, not paralysed, when the question isn’t yet well-defined.

Strong advantage

• Experience in payments, fintech, or financial services – familiarity with interchange, scheme rules, authorisation flows, settlement, or card issuing/acquiring.
• Proficiency in Python or R for statistical analysis, data manipulation, or modelling.
• Experience with modern analytics engineering tooling (e.g. dbt, version-controlled transformations, CI/CD for data).
• Familiarity with unit economics, margin analysis, or P&L-level thinking in a transactional business.

Bonus

• Exposure to payment routing optimisation, decline recovery, or acceptance rate analytics.
• Familiarity with experimentation platforms (LaunchDarkly, Optimizely, or equivalent).

• High-impact, high-volume domain – every transaction at Zilch passes through your surface area. Your work will be felt in the P&L.
• True partnership, not a service desk – you’ll be embedded with PMs as their equal, not downstream taking tickets. Your insight shapes the roadmap.
• Autonomy with support – you’ll operate with significant independence day-to-day, backed by a Lead Product Analyst and two other Spend analysts for collaboration, peer review, and knowledge-sharing.
• Growth trajectory – this role sits at the intersection of payments, product, and commercial strategy. It’s a path toward lead/principal IC or people management depending on your ambition.
• Modern stack – Snowflake, dbt, Looker, LaunchDarkly, Mixpanel, Python – with a Data Engineering team investing in pipeline quality and self-serve infrastructure.