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Data Analyst at PalmPay

PalmPayLagos, Nigeria Data and Artificial Intelligence
Full Time

At PalmPay, we want to provide a financial ecosystem that is open to as many people as possible, and that’s why the only requirement to access financial services from us is that you have a smartphone. We have exclusively partnered with TECNO Mobile, Africa’s leading mobile phone brand with over 50% market share on the continent. The PalmPay app will come pre-installed on over 20 million devices in 2020.

We are looking for a talented Data Analyst to support our data-driven decision-making processes. The ideal candidate will have a strong analytical mindset, exceptional problem-solving skills, and a passion for transforming raw data into actionable insights. As a Data Analyst as Palmpay Limited, you will play a key role in optimizing operations, enhancing customers experience, and driving strategic business initiatives.

Responsibilities:

  • Collect, clean, and preprocess data from multiple sources to ensure data accuracy and integrity.
  • Perform exploratory data analysis to identify trends, patterns, and anomalies.
  • Develop and maintain dashboards, reports, and visualizations to communicate insights to stakeholders.
  • Conduct statistical analysis and hypothesis testing to extract actionable insights from data.
  • Collaborate with cross-functional teams to understand business requirements and provide data-driven solutions.
  • Identify opportunities for process improvement and automation to streamline data workflows.
  • Stay current with industry trends and best practices in data analysis and visualization.

Qualifications:

  • Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, or Economics.
  • 2-3 years of experience in data analysis or a related field.
  • Proficiency in SQL for data extraction and manipulation.
  • Strong analytical skills with the ability to translate complex data into actionable insights.
  • Experience with data visualization tools such as Tableau, Power BI, or Python libraries (e.g., matplotlib, seaborn).
  • Familiarity with statistical concepts and techniques.
  • Excellent communication and presentation skills with the ability to effectively convey technical information to non-technical stakeholders.
  • Detail-oriented and highly organized with the ability to manage multiple tasks and deadlines effectively.

Method of Application

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