Naveen Kumar Maurya

Involved in a 5-member team in daily Agile scrum meetings, adopting methodologies via JIRA resulting in 40% improvement for effective task management & accomplishment. Performed EDA, data cleaning, data processing and various data analytics on CRM data. Implemented Classification ML Algorithms and Bagging & Boosting techniques, achieving an 85% accuracy in lead score prediction, leading to 40% time saving and 25% higher conversion rate. Collaborated with the Business Analysis team, gathered project feature requirements, developed ML/DL Model for real estate price predication with 90% accuracy & trend analysis, deployed in Flask API in AWS EC2 instance, which made the sales team to do better negotiation up to 20% in resale properties. Build web crawlers for data gathering which saved 12k $/ year, used several NLP techniques for language translation, sentiment analysis, text summarizing & name entity recognition (NER). Statistical testing was done on the data, enabling the business team to make decisions 25% faster. Delivered crucial insights using Power BI real-time dashboards with data modeling done using Fact & Dimension Tables and Power Query for ETL.

Car Price Prediction: Excelled in Python for data tasks and implemented ML algorithms, achieving 94% R2 score. Credit Card Customer Segmentation: Applied Python, K-means, and H-clustering for profitable segmentation, achieving a Silhouette Coefficient of 0.51. Telecom User Churn: Using Pandas and ML algorithms, achieved a recall score of 80% for predicting customer churn. Recommendation System: Build an item-item collaborative filtering model in Python, utilizing TF-IDF vectorization and Gretel Synthetic Data Generation for enhanced accuracy up to 20%. Mall Entry Data Analysis: Developed MySQL Data Warehouse, transforming unstructured data into Fact and Dimension tables, and created Power BI dashboards, resulting parking management become 50% easier.