Rajesh Kotwal

Background

About Rajesh Kotwal

data analyst with 6 years of experience in analysing complex data sets and providing valuable insights to improve business decision-making. proficient in sql, python, excel, dash boarding, statistical analysis, data modelling, data visualization, master data management (reltio). strong communication skills and ability to present technical information to non-technical stakeholders. data analyst consultant srs business solution [june-2023 to present]- data architecture for master data management (mdm): leveraged reltio platform for effective management of data, ensuring accuracy, consistency, and reliability across various datasets, thereby enhancing decision-making processes. built brand customer life cycle: the brand customer life cycle project employed a customer lifecycle framework to identify brand specific customer segments and behaviours. it provided actionable insights on adoption, loyalty, and attrition drivers and devised customer-centric metrics for performance tracking. data scientist consultant [myntra][jan-2019 to june-2023] • revenue attribution funnel model: developed a revenue attribution funnel model that tracked major product and merchandising performance, and improved display ads roi by 22%. • product clustering: built product clusters purely based on product attributes to support business use case around assortment planning, demand estimation, product cluster performance based on existing kpis, etc. used various clustering algorithms like k-means, k modes, hierarchical clustering and a combination of k-means and hierarchical clustering and did a comparative analysis to determine the quality of the clusters, using different scores. • brand affinity model: the brand affinity model project used the apriori algorithm to identify customer behaviour for each brand and devised brand penetration by measuring user confidence in purchasing from different brands. • designed framework to improve roi of monetization through product list ads (pla)]: conducted several pla ab experiments and performed statistical analysis to determine the most effective ads placement on the list/search page, without compromising the list to pdp conversion rate. resulting in maximizing the revenue generated by ads. • automated reporting infrastructure using python during sale events by writing optimized sql queries, resulting in hourly reporting. automated the generation of a/b experiment analysis reports, saving 3-5 hours per experiment.