Nandan Kumar Email & Phone Number

Bengaluru, Karnataka, India

In my role as Lead Business Analyst at eBay in Bengaluru, Karnataka, I spearheaded analytics initiatives, leveraging data to drive business decisions. I collaborated with stakeholders to deliver advanced analytics solutions, showcasing my expertise in data mining and dashboarding. My contributions played a key role in enhancing the company's data-driven approach and decision-making processes.Managing a substantial claim resolution portfolio, developing strategies to enhance profitability and maximize returns for the company.Led a team to build seller protections and seller action framework, contributing significantly to the company’s revenue growth.Collaborated with the marketing team to optimize notification channels, resulting in a marked improvement in user engagement.Provided detailed impact reports on potential negative user experiences to eBay leadership, influencing the integration of feature enhancements into product roadmaps.

Bengaluru, Karnataka, India

Knowledge Transfer Roadmap: Developed and implemented a comprehensive roadmap for seamless knowledge transfer between teams, ensuring continuity and minimizing disruptions.Ad Campaign Performance Reporting: Designed and generated detailed reports for the Ads team to effectively monitor and assess campaign performance metrics.Marketing Support: Provided the marketing team with a summarized view of campaign performance, enabling quicker decision-making and strategy adjustments.Efficiency Improvement: Streamlined data analysis processes by creating efficient data tables from larger data sources, reducing analysis time significantly.

Bangalore

Worked with Engineering team to design and automate SMS carrier rate sheet flowing from mailbox to internal database. Helped in reducing the discrepancy between invoices and reporting db from 33% to 4%Developed a report to monitor the SMS Conversion for different carriers and countries. Created alerts for decrease in delivery rate. This report helped in on-time and quick fixing of any error originating from Plivo/Carrier end and reduced average daily complaints from 10 to 2.End to end development of Support team dashboard. Moved data from Freshdesk onto Redshift, defined key metrics and created a Tableau report for customer support tickets. This report was consumed by Support Managers to monitor customer/country/engineer/severity level progress on tickets raised on the Plivo portal.Setup funnel view for Customer on boarding and first payment. Investigated the key milestones responsible for the drop in percentage and suggested measures of improvement to the stakeholder.Developed SaaS metrics for Plivo as first project in the company. Helped in defining key metrics like Churn Customer, Growth Customer, Active Customers and created a report used as Report Card for the company.

Gurgaon, Haryana, India

• Responsible for performing complex data discovery involving system, process and behavioral analysis of critical data items to identify improvement actions to uplift critical data items which enable customer and commercial outcomes• Developing automated data jobs for data cleaning, data validation and data mastership to protectand improve the data asset.• Evolve and drive root cause resolution actions including the creation of business cases to secure investment plan funding.• Responsible for providing the insight that enables the prioritisation via the governance process of data improvement actions.• Working on various technologies like SAS Dataflux, VBA, Teradata and Hadoop for gathering data,creating data repository, analysing it and delivering quality outputs in the form of dashboard to the client. • Interacting closely with client to understand the project requirements, developing a data perspective, ensuring quality deliverables along with understanding the business requirement. • Migrating existing BAU’s from Teradata to SAS Dataflux to reduce data processing time. • Identifying Data Anomalies and Outliers present in the datasets using SAS Dataflux. • Ad-hoc Analysis for skewed, missing and mismanaged data fields for customer data with meaningful insights to support business functions and Third party data purchase. • Identified customers whose communication preference can be converted to digital leading to costsaving.