Senior Data Analyst

Kuda is a money app for Africans on a mission to make financial services accessible, affordable and rewarding for every African on the planet.
We’re a tribe of passionate and diverse people who dreamed of building an inclusive money app that Africans would love so it’s only right that we ended up with the name ‘Kuda’ which means ‘love’ in Shona, a language spoken in the southern part of Africa.
We’re giving Africans around the world a better alternative to traditional finance by delivering money transfers, smart budgeting and instant access to credit through digital devices.
We’ve raised over $90 million from some of the world's most respected institutional investors, and we’re rolling out our game-changing services globally from our offices in Nigeria, South Africa, and the UK.

Role Overview

Kuda is looking for a highly skilled and motivated Senior Data Analyst to join our growing BI & Analytics team. We are looking for someone who can work with large datasets, leverage their expertise in data analysis and deliver actionable insights across various business functions. You will play a critical role in helping to shape data-driven decisions around attribution optimisation, product performance, experimentation and user engagement. 

Roles and responsibilities

• Develop, own and champion how we leverage data from our tech stack. 
• Analyze, and where required build, datasets that enable better understanding of company KPIs, marketing performance and user engagement.
• Design, develop, and maintain dashboards and reports using tools like Looker.
• Conduct in-depth analyses to improve customer acquisition, engagement, retention, referral, segmentation and revenue across multiple channels. Understand trends, correlations and identify opportunities to move these key user growth metrics. 
• Perform exploratory data analysis (EDA) and statistical modeling to support strategic initiatives.
• Ensure the accuracy and relevance of key performance indicators (KPIs) across different functions. 
• Design and analyze experiments to improve user acquisition, product adoption, and spend efficiency of marketing campaigns.
• Be comfortable with cross-functional collaboration and delivery. 
• Present findings and recommendations clearly to both technical and non-technical audiences.