As a Data Analyst you will work cross-functionally with Product, Marketing, Finance, and Customer Support teams to provide insights that directly impact strategic decisions (influencing product improvements, marketing efficiency, etc), customer satisfaction, and business performance.
The ideal candidate is highly analytical, curious, and passionate about driving insights through Collaborate with Product, Marketing, Customer Support, and Finance teams to understand analytical needs and deliver actionable insights.
- Analyze user behavior through acquisition and retention funnels including registrations, activations, top-ups, and churn.
- Work with geo-segmented data to evaluate regional performance trends and provide actionable insights for location-specific growth strategies.
- Conduct cost-benefit analyses, market trend assessments, and customer support ticketing analytics to improve business operations and user satisfaction.
- Develop, automate, and maintain dashboards and reports to track KPIs and business performance metrics.
- Query large datasets to uncover insights, trends, and anomalies.
- Lead initiatives on data ingestion from web sources to support market intelligence.
- Ensure data accuracy, consistency, and quality across various systems and touchpoints.
- Support forecasting and strategic planning with robust, data-backed models.
- Document methodologies, models, and business logic for transparency and reproducibility.
- Present data insights in a cohesive, simple, and visually engaging format to drive clarity and decision-making across teams.
Required Skills :
Bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics).5+ years of experience in a data analyst or business intelligence role.Expert SQL skills and comfort working in cloud-based data warehouses, such as Google BigQuery.Proficiency in Google Analytics (GA4).Proficiency in dashboards such as Tableau, Power BI, and Looker Studio.Strong storytelling and data visualization skills.Excellent communication skills with the ability to distill complex data into clear business insights.Familiarity with causal inference models and experimentation frameworks is a plus.Prior experience in a consumer-tech, travel, or telecom environment.Some experience in designing and analyzing experiments or A / B tests is a plus.Past experience with marketing analytics platforms and / or events-based analytics (e.g., Google Ads, Meta Ads, Adjust), with a strong understanding of how to extract and interpret user data across channels to form meaningful insights into the user journey.Experience with Python or R is a plus.(ref : hirist.tech)