S

Data Analytics Tutor - OnSite - Akure

SupportPro [By SalesPlat]

Research, Teaching & Training

Today
New
Min Qualification: Experience Level: Mid level Experience Length: 3 years

Job descriptions & requirements


Job Title: Data Analyst

Location: Akure - Fully

Work Mode: Onsite (3 days a week)

Salary: #80,000


Background: Data Visualization, Business Intelligence, Excel & SQL, Power BI / Tableau, Statistical Analysis, Reporting & Insights, Process Optimization, Decision Making, Forecasting & Trend Analysis, Problem Solving


The Data Analyst will be responsible for 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


• 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.

• 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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