Data Analyst - Akure / On-Site

Job Title: Data Analyst

Location: Akure

Work Mode: On-Site

Salary: From #75,000

Background: Data Visualization, Business Intelligence, Training

The Data Analyst will be responsible for training students, collecting, analyzing, and interpreting large datasets to support business decision-making.

This role involves building dashboards, identifying trends, improving data processes, and providing insights that drive organizational growth.

Responsibilities

• Train entry level students into data analysts, Collect, clean, and organize data from multiple sources (databases, APIs, spreadsheets).

• Analyze data trends and patterns to support business decisions.

• Develop dashboards, reports, and visualizations using tools such as Power BI, Tableau, or Excel.

• Work with cross-functional teams (Product, Marketing, Finance, Operations) to identify data needs.

• Build and maintain automated data pipelines.

• Generate periodic reports (daily/weekly/monthly) on key performance indicators (KPIs).

• Identify data gaps and recommend process improvements.

• Ensure data accuracy, integrity, and security.

• Translate complex data findings into simplified reports for non-technical stakeholders.

• Support forecasting and predictive analysis projects.

Requirements

• Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, Mathematics, or related field.

• 2–3 years experience as a Data Analyst or similar role (junior roles can remove experience requirement).

• Strong proficiency in Excel/Google Sheets.

• Experience with SQL for querying databases.

• Knowledge of data visualization tools (Power BI, Tableau, Looker, Excel).

• Experience with Python or R for data analysis is an added advantage.

• Familiarity with data cleaning, validation, and transformation techniques.

• Strong analytical and problem-solving skills.

• Excellent attention to detail and accuracy.

• Good communication and presentation skills.

• Ability to work independently and as part of a team.

• Ability to translate data insights into actionable recommendations.

• Experience with machine learning or predictive modeling.

• Knowledge of statistical analysis.

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