Data Analysis & Insights
Analyze key performance metrics such as conversion rates (e.g., Trial to Buyer), retention rates, and campaign ROI to uncover trends and growth opportunities.
Work closely with leadership to provide interpretative analysis that drives revenue, customer retention, and new market penetration strategies.
Collaborate with marketing and partnerships teams to validate and monitor campaign effectiveness.
Strategic Decision Support
Build predictive models and dashboards to forecast growth, set benchmarks, and monitor success metrics.
Partner with teams across to support initiatives with real-time insights and data validation.
Deliver insightful reports and presentations that simplify complex data into actionable recommendations for directors and senior stakeholders.
Data Reporting & Visualization
Leverage tools like Tableau, Power BI, or similar to create visual dashboards and real-time reporting systems.
Ensure the delivery of easy-to-understand, high-impact dashboards tailored for non-technical teams and senior management.
Collaborate with data engineers to streamline ETL pipelines and ensure data accuracy for reporting purposes.
Cross-Functional Collaboration
Work alongside technical teams (e.g., data engineers and ETL specialists) to ensure data readiness.
Provide continuous training and support to internal teams to enable them to use data insights effectively.
Bridge the gap between raw data processing and strategic planning by translating data into business narratives.
Skills & Qualifications
Must-Have
Strong business acumen with the ability to connect data insights to business objectives.
Proficiency in data visualization tools like Tableau, Power BI, or similar.
Experience with data analysis techniques, including statistical analysis, trend analysis, and predictive modeling.
Strong skills in data interpretation and delivering clear, actionable recommendations to senior stakeholders.
Advanced skills in SQL and Excel for querying and analyzing datasets.
Nice-to-Have
Exposure to ETL processes or experience working alongside data engineers.
Knowledge of tools like Python or R for advanced data analysis.
Understanding of LMS platforms, customer behavior metrics, or SaaS-based analytics.
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