Dynamic data and business analyst with dual master’s degrees and over 2 years of experience in driving data-informed decision-making and improving operational efficiency in the pharmaceutical industry. Successfully led initiatives resulting in a 15% increase in market share at Panchsheel Organics. I am seeking to leverage my analytical expertise to drive impactful results for a U.S.-based company.
β’ Coursework: Structured/Unstructured Data, SQL, R & Python for Data Analysts, Machine Learning
β’ Notable Projects:
β’ R Programming – Airbnb Text Mining (NLP) & Shiny App View Project: Directed NLP-based text mining analysis on Airbnbβs
dataset, achieving 75% accuracy in identifying guest preferences. Designed a Shiny dashboard that enhanced marketing strategies and
service personalization, improving decision-making speed by 20%.
β’ Python – Production Prediction View Project: Improved forecast accuracy by 15% through advanced predictive modeling and
contributed to a 10% boost in operational efficiency with strategic recommendations based on thorough data analysis.
β’ SQL Queries β H1B Visas View Project: Identified top-paying roles and strategic employment opportunities in New York through SQL
analysis, providing F1 students with actionable insights for optimizing their job search in the U.S. market.
β’ Coursework: Data Visualization & Analysis, Analyzing Business, Financial Decision Making
β’ Notable Projects:
β’ Tableau β Data Visualization View Project: Developed comprehensive visualizations and presentations covering data storyboarding,
graph selection, and effective visual design. Increased data comprehension and decision-making efficiency by 25% among stakeholders.
β’ Coursework: RDBMS & Oracle, Accounting, Financial Management
β’ Increased stakeholder engagement by 20% through the development of compelling, data-driven visual narratives using Tableau, Power BI, and SAP Analytics Cloud (SAC).
β’ Enhanced data accuracy by 15% by mastering data cleaning, manipulation, and statistical analysis using Excel, SQL, and Python.
β’ Streamlined data processing by integrating diverse sources with Datasphere, improving operational efficiency by 10%.
β’ Elevated project success rates by 12% through generating detailed reports and interactive dashboards that communicated complex findings.
β’ Pursuing certifications in business intelligence and analytical tools, aiming for 100% proficiency by year-end to enhance analytical capabilities.
β’ Boosted sales forecast accuracy by 18% by developing and maintaining business intelligence dashboards using Python, R, and SQL.
β’ Identified key trends that led to a 14% increase in market share for API products through in-depth analysis of sales and production data using Python’s pandas library, R’s ggplot2, and SQL.
β’ Automated data processes, reducing preparation time by 30%, which contributed to a 14% increase in market share.
β’ Improved process efficiency by 20% by leading cross-functional workshops to gather requirements for system enhancements.
β’ Developed statistical models for sales and production data analysis, contributing to a 14% market share increase.