Conducted classroom lectures to teach data analysis and visualization concepts using Tableau. Additionally, supported the professor in managing class logistics, monitoring participation, and evaluating assignments.

● Executed end-to-end data & dashboard migration from Cloudtail to Amazon ecosystem utilizing S3 & Quick sight infrastructure in AWS suite ensuring visibility to $32 million business.● Partnered with legal team to generate key summary analyses for the perusal of Competition commission of India.● Consolidated disjoint data streams from multiple APIs into a holistic Quick sight dashboard representing live profitability metrics for Prime day which resulted in +4% margin benefit and conservation of 50 workhours/week.

● Segmented vendor pool to multiple cohort’s basis delivery patterns and designed a custom entitlement framework to drive vendor negotiations and cost recovery. Recovered $6.25 Million - FY 21 (24% YoY)● Formulated & maintained weekly & monthly business reporting process encompassing 40+ crucial KPI’s across various business spectrums which provided operational & business visibility to senior executives.● Built real time recommendation engine using SQL & Qlik sense for promotional & holiday events to dispatch/curtail excess purchase orders and track price matching impact resulting in +6% net margin benefit.● Co-owned profitability analytics programs such as MRP correction, Amazon combos & selection economics which conserved a leakage revenue of $9 Mn – FY 21 (65% YoY) and improved inventory turnover.

Client: Walmart, Inc.Conceptualized granular activity-based cost to serve model in Hadoop infrastructure to identify true profitability of an item and inefficiencies in supply chain costs resulting in $5 million freight cost reduction – FY 18● Established automated data pipelines to migrate information from Teradata to Hadoop at a set frequency. ● Built an anomaly detection framework using shape-based clustering to flag outliers in cost components.Developed an assortment recommendation engine to suggest localized assortment for China hypermarkets which improved store traffic by 14% and increased recency, frequency & monetary value across customer segments.● Identified association/substitutability behaviors amongst products by implementing agglomerative hierarchical decision tree technique inserting purchase, product & previous assortment layout attributes. ● Delivered optimized assortment at store cohort level through bilingual R shiny dashboard consisting of custom functions to optimize the assortment based on business goals.Client: Mars, Inc.Modelled an ARIMA demand forecasting framework to predict future orders of key product lines from retailers to achieve the target service level. Benchmarked with existing model and observed +11% improvement in accuracy.