I am a motivated professional possessing strong analytical aptitude and expertise in tools for data driven solutions. Prior to this, I was working as a Data Analyst in a reputed Supply Chain Management company, where I leveraged my analytical skills towards driving the productivity of the company with data driven solutions. During my time with the Business Intelligence team, I was responsible for performing various data exploratory analysis, assisted in understanding the business trends and helped in identifying the key pivotal points leading to taking important business decisions by the management and accelerating the overall growth.
As as Data Analyst Intern at T-Mobile, I was working with the Business Intelligence team and built various dashboards in tracking our daily subscribers activity for the business users. Working in an agile environment with the most talented people brought the best in me during the internship period.
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Experience
Data Analyst Intern
T-Mobile US, Richardson, TX June 2019 – September 2019
• Collaborated with business teams & SME on agile basis in gathering the data requirements to help drive insights
• Designed, built and maintained end to end data pipelines by collecting the subscriber’s data from disparate sources & created data models in QVDs by writing ETL scripts
• Developed 5 Qlik Apps to bring visibility across 18M subscriber’s activity on various KPI’s with 10x faster load speeds
• Developed high accuracy model to predict rebate estimate on 50 M records by utilising ML models using PySpark, Spark SQL & Spark MLlib on Azure Databricks cloud platform leading to effective promotion and cost savings by 5%
• Presented Qlik story to over 50 professionals at T-Mobile during Brown Bag on selecting the right visualization for different applications to produce quicker insights
Data Analyst
Future Supply Chain Solutions Ltd, Mumbai, India June 2016 – May 2017
• Analyzed the supply chain data worth of $15M using SQL, Python and Spark ML, following Agile SDLC methodologies to extract insights, study customer behavior and purchase trends
• Designed and deployed data pipelines to collect the TMS data from multiple sources and created high-performance, efficient aggregates for storing the supply chain data using Spark, Python and Teradata
• Developed 5 interactive Tableau workbooks indicating around 50 business metrics for supply chain analytics
• Partnered with cross-functional teams to prepare Business Requirement documents
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Projects
1. Predicting profitable zipcodes for investment on Airbnb and Zillow data (Python, Tableau)
• Performed data quality check by removing outliers, imputing missing fields using appropriate statistical techniques, transforming skewed distribution, detecting irregularities and fixing it
• Performed breakeven and appreciation analysis, selected the top zipcodes to invest in 2-bedroom properties
2. Sales Prediction on Store level Mayonnaise data (SAS, Tableau, Machine Learning)
• Implemented various statistical analysis such as hypothesis testing, Chi-sq test, t-test, ANOVA, Hausman test
• Performed linear regression by taking in top significant features, used polynomial features to increase R sq to 0.82
• Performed conditional logit and survival analysis in predicting the loyal customers and provided recommendations