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Lead Data Analyst - Spend Economics

Salary

75 - 100 GBP

Min Experience

0 years

Location

Worship Square, 65 Clifton Street, London, United Kingdom

JobType

full-time

About the job

Info This job is sourced from a job board

About the role

We're looking for a Lead Data Analyst (Individual Contributor) to join the Spend Squad. The Spend Squad enables our customers to spend from their Wise accounts in a sustainable manner, ensuring that we're able to grow our product in-line with our squad-level KPIs. The Wise Card was first launched in Europe in 2018, allowing customers to spend internationally at the mid-market rate, with only a low, upfront conversion fee. Since then, we've expanded to over 50+ countries and territories in the Americas and APAC, and built features like instant issuance of digital cards and enhanced spending controls. We've issued more than 4 million cards that are being used in over 160 countries every minute. Derive insights for Spend Economics: Deep-dive into transaction-level data to understand customer behaviour, payment patterns, and spend drivers to ensure sustainable unit economics. Improve and develop our Data Models for Spend Economics to scalably and accurately forecast unit economics, identify root causes of shifts in key metrics, and surface actionable insights that drive decisions. Mentoring junior analysts, fostering best practices in product analytics, and champion data-informed decision-making across the Spend domain. Partner with the Finance team to understand our unit cost trend analysis and inputs to our model Help your team make data-driven decisions and prioritise the most impactful opportunities to enable Wise to reach Mission Zero

About the company

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.

Skills

sql
data warehouse
dbt
financial forecasting
product thinking
data-driven decision making
data analysis