Data Analyst II

About the role

You will own the end-to-end analytics lifecycle for core payment intelligence products at GoCardless, defining questions, shaping datasets, and delivering actionable insights that directly influence product strategy and commercial outcomes. You will partner tightly with Product Managers, Engineers, and Data Scientists to design experiments, track user behaviour, and translate complex findings into clear narratives that guide executive decision-making. This role requires you to iterate on reports and dashboards, ensuring stakeholders across operations, marketing, and commercial teams have reliable, self-serve access to data that drives decisions. You will build and maintain models of customer behaviour, such as segmentation and lifetime value, to safeguard customers from fraud and improve payment success. You will act as a mentor within the organisation, elevating data standards and tracking best practices so that the entire business becomes more data-driven over time. You will continuously explore AI and automation opportunities, leveraging tools like Gemini to enhance analysis quality and payment experiences. Ultimately, you will unlock new layers of payment intelligence that protect revenue and strengthen GoCardless as the trusted payment partner for businesses worldwide.

Key facts

What you'll do

Analyse large-scale user and payment data to generate insight that drives measurable business outcomes for GoCardless products.

Define and own key performance indicators, designing tracking frameworks and leading experiments to evaluate product success and user behaviour.

Champion Product Data coverage across systems, setting standards and mentoring cross-functional teams to embed data-driven practices in their workflows.

Build and refine user-segmentation models and customer lifetime value frameworks to inform strategic product and commercial decisions.

Leverage SQL, visualisation tools, and automation scripts to streamline data pipelines and ensure timely, accurate insight delivery.

Collaborate with Data Scientists and Engineers to integrate AI capabilities, such as Gemini, into analysis workflows and improve fraud detection and payment recovery.

Translate technical findings into high-impact narratives that influence product roadmaps, steering discussions across product, commercial, and executive stakeholders.

Establish best practices for tracking and reporting, creating reusable assets that scale as GoCardless expands into new markets and product lines.

Monitor leading indicators of user behaviour to anticipate churn, identify growth opportunities, and protect customers from bad outcomes like payment failures and fraud.

Champion a culture of experimentation, using A/B testing and continuous iteration to validate hypotheses and maximise the effectiveness of payment intelligence features.

Ensure insights are delivered through robust dashboards in Looker, enabling stakeholders to make confident, data-backed decisions on product investments.

Maintain a deep understanding of existing payment intelligence products such as Protect+ and Success+, identifying opportunities to enhance their accuracy and business impact.

Partner with commercial and operations teams to align data strategy with revenue goals, improving collection performance and reducing financial risk.

Continuously explore emerging AI and automation techniques to enhance analysis speed, insight depth, and the overall payment experience for customers.

Requirements

You have a Bachelor's degree in a quantitative field such as Mathematics, Statistics, Computer Science, Economics, or a related discipline.

You have 2+ years of professional experience in a data analyst or analytics-focused role, with a proven track record of delivering insights that influence business decisions.

You are highly proficient in SQL and comfortable writing complex queries to manipulate large datasets across distributed systems.

You have hands-on experience with at least one modern data visualisation tool such as Looker, Tableau, or Power BI.

You understand fundamental statistical concepts and have used A/B testing frameworks to evaluate product changes and user behaviour.

You have experience working with programming languages such as Python for data wrangling, analysis, and automation.

You are familiar with machine learning concepts and have worked with tools like Gemini or similar AI platforms to enhance analysis or decision-making.

You have a strong grasp of customer analytics, including segmentation, cohort analysis, and lifetime value modelling in a payments or subscription context.

You demonstrate strong communication skills, able to translate technical findings into clear recommendations for non-technical stakeholders.

Nice to have

Experience with payment systems, direct debit, or banking infrastructure.

Deep knowledge of AI techniques and prompt engineering for analytical tasks.

Background in fraud detection, risk management, or compliance analytics.

Familiarity with commercial finance, billing, or revenue operations in a subscription environment.

Experience contributing to open source projects or publishing internal insights as documentation or talks.

Practical notes

This is a full-time position based in Riga, Latvia.

Relocation support and visa sponsorship may be available for eligible candidates.

The role reports to the Payment Intelligence leadership team and requires regular collaboration across time zones.