Lead Product Analyst - Business Onboarding at Wise

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

24 Aug, 26

Salary

115000.0

Posted On

26 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Funnel Analysis, Customer Segmentation, Cohort Analysis, Metrics Decomposition, Experimentation, Causal Inference, Product Opportunity Sizing, dbt, Airflow, Semantic Layers, Metric Stores, LLM Data Foundations, A/B Testing, KYC/KYB Processes, Data Visualization

Industry

Financial Services

Description

Company Description About Wise Wise is a global technology company, building the best way to move and manage the world’s money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their life easier and save them money. As part of our team, you will be helping us create an entirely new network for the world's money. For everyone, everywhere. More about our mission. Job Description We’re looking for a Lead Product Analyst to join the Business Account squad and the Business Onboarding team. As a Lead Product Analyst, your mission will be to deeply understand the needs of business customers as they register with Wise for the first time, regain access to their account, and complete the checks needed to use Wise safely. You’ll help the team find the right balance between conversion, customer experience, operational efficiency, and risk controls: reducing unnecessary friction for legitimate businesses while helping deflect bad actors. This role offers a significant opportunity to collaborate across various teams, including Business Pricing, Account Experience, and Verification, to ensure a seamless and integrated experience for our business customers. For more information on our Analytics Career Map and levelling structure, click here. What you will be doing: Own the KPI tree and core metrics for business onboarding, ensuring alignment. Help your team understand their progress and communicate recommendations to senior stakeholders. Use data exploration and funnel analysis to identify high-impact opportunities in the onboarding flow. Partner with the team to prioritise projects with the highest leverage. Lead experimentation and A/B tests for business onboarding, defining hypotheses and metrics. Analyze results to drive product roadmap recommendations to reduce friction and boost conversion. Build and maintain data products and dashboards to empower self-service data literacy for PMs, design researchers and engineers. Design LLM-ready data foundations for onboarding analytics, including clean business entities, event schemas, semantic definitions, metadata, retrieval-friendly documentation, and evaluation datasets that make data usable by AI systems without losing governance or context. Partnering with your product manager, engineers and designers throughout the product development lifecycle to build and iterate product changes based on your insights Qualifications What you’ll bring: Technical depth: 5+ years of experience in analytical roles, with excellent SQL and the ability to write clear, performant, reliable queries across large and complex datasets. Product analytics craft: Strong experience with at least three of funnel analysis, customer segmentation, cohort analysis, metrics decomposition, experimentation, causal inference, or product opportunity sizing. Data product ownership: Experience building and owning production-grade analytical assets, such as dbt models, Airflow jobs, semantic layers, metric stores, governed dashboards, or trusted self-serve datasets. LLM-ready data thinking: You understand what makes data usable by AI systems: clean entities, stable identifiers, clear definitions, metadata, access controls, provenance, quality tests, and documentation that can be retrieved and reasoned over. Ownership: You enjoy working independently in a fast-paced environment. You identify high-impact opportunities and make them happen. You triage requests by impact and know when to go deep versus deliver 80/20 results. Communication: Excellent verbal and written communicator - you cut through the noise, communicating what matters in a way that people get it. You craft dashboards and visualisations that tell a story and have diagnostic power. Analytical Thinking: You have experience with at least one of: funnel analysis, customer segmentation/cohort analysis, or metrics decomposition. You structure problems before diving into data and know how to find the signal in the noise. Nice to have but not essential: Prior experience in the B2B space - understanding business customers’ financial and operational needs. A/B testing or causal inference experience. Familiar with onboarding frameworks and KYC/KYB processes. Demonstrated capability to utilize AI and machine learning for enhancing analytical results and automating routine work. Additional Information What do we offer: Salary: £75,000 - £115,000 Company Restricted Stock Units Numerous great benefits in our London office Key benefits: Hybrid working Paid annual holiday, sick days, parental leave and other leave opportunities 6 weeks of paid sabbatical after 4 years at Wise on top of annual leave For everyone, everywhere. We're people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive. We're proud to have a truly international team, and we celebrate our differences. Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers. If you want to find out more about what it's like to work at Wise visit Wise.Jobs. Keep up to date with life at Wise by following us on LinkedIn and Instagram. Compensation: GBP 75000 - GBP 115000 - yearly

Responsibilities

Own the KPI tree and core metrics for business onboarding to optimize conversion and customer experience. Lead experimentation and build data products to empower self-service analytics and AI-ready data foundations.