We are looking for a detail-oriented and analytical Data Insights Analyst to transform complex data into actionable insights that drive strategic business decisions. In this role, you will collect, analyze, and interpret data across various business functions, enabling teams to make informed decisions and optimize performance. You will collaborate with stakeholders to ensure insights are accurate, relevant, and impactful.
Key Responsibilities
- Collect, clean, and analyze data from multiple sources to uncover trends, patterns, and insights.
- Develop dashboards, reports, and visualizations to communicate key findings to stakeholders.
- Collaborate with business teams to understand data needs and translate them into analytical solutions.
- Conduct ad-hoc to support business initiatives, campaigns, and strategic decisions.
- Monitor KPIs and metrics, providing actionable recommendations for performance improvement.
- Support data-driven decision-making by presenting insights in a clear and compelling manner.
- Work with data engineering and IT teams to ensure data quality, accuracy, and accessibility.
- Stay updated on best practices, tools, and emerging trends in data analytics and visualization.
Qualifications & Requirements
- Bachelor’s degree in Statistics, Data Science, Business, Economics, or a related field; Master’s is a plus.
- 2–5 years of experience in data analysis, business intelligence, or a related role.
- Proficiency in SQL, Excel, Python/R, and BI tools (Tableau, Power BI, Looker, etc.).
- Strong analytical, problem-solving, and critical-thinking skills.
- Excellent communication and presentation skills to convey insights effectively.
- Detail-oriented, organized, and capable of managing multiple projects simultaneously.
- Proactive, curious, and data-driven mindset.
Key Performance Indicators (KPIs)
- Accuracy, relevance, and timeliness of reports and insights.
- Number of actionable insights provided that influence business decisions.
- Improvement in business performance metrics based on data-driven recommendations.
- Stakeholder satisfaction with analysis, visualizations, and reporting outputs.
- Data integrity and quality across analytics platforms and dashboards.