Data analyst with experience in data analysis, Tableau dashboard development, predictive modeling, and machine learning. Has completed internships in data analytics and business analytics, and holds a B.Tech in Electrica…
Data analyst with experience in data analysis, Tableau dashboard development, predictive modeling, and machine learning. Has completed internships in data analytics and business analytics, and holds a B.Tech in Electrical Engineering from Maulana Azad National Institute of Technology Bhopal.
As a Data Analyst at American Chase, I conducted a meticulous Trending Job Market Analysis, processing data from 10,000+ job listings. I identified a 15% increase in remote job postings and a 20% YoY growth in data science-related roles. Leveraging Tableau, I created 20+ interactive dashboards for effective data-driven decision-making. Additionally, I developed a predictive model with an 85% accuracy rate for forecasting job market trends. These efforts greatly influenced talent acquisition and workforce planning strategies.
Conducted Trending Job Market Analysis, processing data from 10,000+ job listings.
Identified a 15% increase in remote job postings and 20% YoY growth in data science roles.
Created 20+ interactive Tableau dashboards for data-driven decision-making.
Developed a predictive model with 85% accuracy for job market trend forecasting.
Influenced talent acquisition and workforce planning strategies significantly.
Developed and implemented unsupervised and supervised learning models during the internship.
Achieved 85% accuracy in unsupervised clustering, identifying 5 distinct patterns in a dataset of 10k records.
Employed supervised learning techniques, attaining 90% accuracy in predicting target variables.
Constructed and assessed 10+ predictive models using classification algorithms, such as Logistic Regression and Random Forest, to identify the best-performing model with an accuracy of 85%.
Collaborated with a team of 5 data analysts and developers to streamline the data processing and model deployment workflow.
Resulted in a 50% reduction in development time and a 30% improvement in data quality.
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