Data Analyst at Workforce Group

Workforce Management Centre Limited is a Management Consulting and Outsourcing Professional Services Firm. Following its inception in July 2004, Workforce Management Centre Limited (Workforce) has built an enviable reputation as the leading indigenous management and professional services consulting firm in Nigeria. Drawing from its Deep Domain Expertise, in the area of organisational effectiveness and employee performance, the Company is positioned to assist businesses across diverse sectors of the economy in their quest to create sustainable value for their stakeholders. At Workforce, we are committed to helping our clients perform at the highest levels and achieve their desired success. We pride ourselves in our ability to consistently adopt structured, rigorous and well thought through diagnostics process focused at understanding the peculiar needs of our clients and then design, develop and deploy customised innovative solutions and interventions to meet those needs. Our service offerings are targeted at both private and public sector organisations in Nigeria, the West African Sub-region, and other organisations across the world seeking value adding solutions to the issues and challenges militating against employee performance and organisational effectiveness. Currently, our client portfolio comprises of 75% of financial institutions in Nigeria, Top 10 FMCG companies in Nigeria Top 5 Telecommunication Service providers in Nigeria. Leading Oil & Gas Companies Leading Advertising & Marketing Communications Companies Leading Real Estate Firms Leading Services and Trading Companies

Role Summary:

• The Data Analyst is responsible for collecting, analyzing, and interpreting large datasets to provide actionable insights that drive business decisions. The role involves data mining, statistical analysis, reporting, and visualization to support various departments in achieving organizational goals.

Key Responsibilities

Data Collection and Preparation

• Gather, clean, and organize data from multiple sources, including databases, spreadsheets, APIs, market research and other systems.
• Validate data accuracy and integrity to ensure reliable analysis and reporting.
• Develop and maintain data pipelines and workflows for consistent data delivery.

Data Analysis and Insights

• Perform exploratory data analysis (EDA) to identify trends, patterns, and outliers.
• Use statistical methods to analyze data and draw meaningful conclusions.
• Provide insights and recommendations to stakeholders by interpreting data and explaining the implications of findings.
• Collaborate with business units to identify key performance indicators (KPIs) and metrics.

Data Visualization and Reporting

• Design and create dashboards, reports, and visualizations using tools like Tableau, Power BI, or Excel.
• Present complex data findings in an easy-to-understand format for non-technical stakeholders.
• Automate recurring reports and optimize data presentation processes

Business Support

• Work with cross-functional teams to support decision-making with data-driven insights.
• Identify areas of improvement in business operations through data analysis.
• Participate in strategic projects and provide analytical support for planning and forecasting

Data Governance and Security

• Ensure compliance with data privacy regulations and company policies. Implement best practices for data management, storage, and sharing.
• Maintain confidentiality and integrity of sensitive information. Continuous Improvement Stay updated with the latest tools, technologies, and trends in data analytics.
• Propose and implement improvements to existing data processes and methodologies.
• Train team members on data tools and analytical techniques as needed

Key Qualifications

Education:

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. A master’s degree or certification in data analytics is an advantage.

Experience:

• 3–5 years of experience in data analysis, business intelligence, or a related field. Proven experience working with large datasets and performing advanced analyses.

Technical Skills:

• Proficiency in data analysis tools such as SQL, Python, R, Tableau, Excel, Power BI, Google Analytics, etc.]
• Experience with data visualization platforms like Tableau, Power BI, or Looker.
• Familiarity with statistical analysis techniques and tools.

Method of Application