$ cat jobs/senior-business-analyst-moniepoint-8f9604162195.json
Senior Business Analyst
Who we are Moniepoint Inc. is Africa’s all-in-one financial platform, helping 20 million businesses and individuals access seamless payments, banking, credit, cross-border, and business management tools each month. As Nigeria’s largest merchant acquirer, we power most of the country’s point-of-sale (POS) transactions. Through our subsidiaries, Moniepoint Inc. processes over $250 billion in digital payment transaction value annually. About the role The Senior Business Analyst plays a key role in shaping the growth and success of Moniepoint ’s payment products. You'll design, test, and implement strategies that improve user acquisition, boost retention, and elevate product engagement. This role blends deep quantitative analysis with collaborative, strategic thinking. You'll partner with teams across the business to ensure our payment solutions meet real market demands and grow efficiently as we scale. Ultimately, you'll make sure our products not only attract users but also scale sustainably to create financial happiness for everyone. Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth. Key Responsibilities Partner closely with product managers, business development, and data engineering teams to help our growth team uncover problems and make product metrics highly visible. Translate complex product and business questions into simple, actionable insights. Build, maintain, and scale self-service dashboards and custom visualisation tools. Own end-to-end analytics for our growth products—from gathering data requirements and estimating opportunity sizes to designing experiments and conducting post-launch impact reviews. Cultivate trusted relationships across teams, acting as a collaborative link between technology, business, and product. Apply advanced mathematical and statistical modelling techniques (including A/B tests, multivariate testing, clustering, and supervised learnin
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