chandragumelar

Led a team of 9 mid-level data analysts and 2 data scientists, working closely with engineering, product, design, and research teams to build pricing models, WMS, TMS, CRM tools. Supported product development by providing data analysis, user insights, and operational feedback. Built dashboards in Superset, Metabase, and Tableau. Established key metrics, developed calculations, and aligned with stakeholders to ensure consistent tracking of product, operational, and business performance. Identified and eliminated bottlenecks across sourcing, procurement, warehouse, logistics, and customer service, supporting better product and operational outcomes. Presented monthly operational performance reports to VPs and cross-functional teams, helping influence decisions across business, product, engineering, and finance. Implemented experimentation frameworks to validate product changes and measure their impact on user experience and operational outcomes. Established a new way of working by transforming the data team from a request-based service into a strategic thought partner, proactively engaging with business teams to drive deeper impact. Optimize logistics costs by analyzing volume, distance, fleet usage, and delivery density. Identified that the cost-to-revenue ratio ranged from 6% to 19%, and through continuous improvements, helped drive better operational efficiency. Linked customer service performance to revenue contribution from retained customers (IDR 4.4B) and potential loss from churn (IDR 5.7B). These insights helped the Customer Service team improved. Introduced aging, shelf life, throughput, and speed metrics to monitor inventory health. Established a baseline of 58%, providing a starting point for future optimization.

Led the decentralization of data analytics by consolidating datasets. Previously, each department had its own analyst, dataset, and dashboards, which led to fragmented insights. Built datamarts and standardized data dimensions to transform raw, unstructured Google Analytics data (hundreds of columns) into an analytics-ready dataset, establishing a single source of truth. Implemented ETL pipeline in BigQuery, leveraging scheduled queries for seamless incremental data updates—achieving a 95% boost in processing efficiency. Built dashboards in Looker to support business, product, and operational teams with clear, actionable insights. Managed and processed over 1 TB of data daily in BigQuery, ensuring reliability, scalability, and efficiency in data operations. Partnered with the data engineering team to optimize queries in BigQuery, reducing costs by nearly 80%—from ~$950/week to ~$150/week—through advanced query tuning, and data partitioning. Fostered a data-driven culture by leading weekly data-driven discussions and creating an analytics newsletter, integrating Business Intelligence insights into strategic decision-making processes.

Built the company’s first dedicated data analytics function from the ground up, enabling more structured decision-making and cross-team collaboration. Served as a key advisor to the CEO by providing data-driven insights to support strategic and operational decisions. Built dashboards in Metabase to provide teams with clear, real-time insights for operational and strategic decision-making. Led weekly data-driven sessions with digital marketing and business teams, where analytics recommendations directly shaped campaign launches and boosting ROI. Implemented social listening tools (SocialBakers), processing and analyzing data to generate actionable insights for stakeholders and enabling a proactive approach to brand perception. Drove analytics-based inventory management across six warehouses, optimizing stock levels, streamlining operations, and achieving 0% stock discrepancies.

Built dashboards in Metabase and Redash to deliver operational, product, and business insights to cross-functional teams. Data analytics for two flagship apps, SwipeRx and SwipeRx B2B, spanning six markets across Southeast Asia (Indonesia, Philippines, Cambodia, Malaysia, Thailand, Vietnam). Reported directly to the COO, providing data-driven insights to support operational and strategic initiatives. Built and prototyped critical analytics tools—including cashback management, customer success tracking, stock analysis, and payment monitoring—that served as MVPs. Streamlined data cleaning processes, reducing data preparation time by 20% for reporting tasks and improving overall efficiency.