BHAVATARINI THANGARAJU

Conducted exploratory data analysis on CRM data to improve feature selection and data quality. Orchestrated data cleaning and NLP processes using NLTK and SentenceTransformer, raising model accuracy to 90%. Built scalable ML pipelines with XGBoost to impute missing profiling data for over 350,000 records, increasing data completeness to 95%. Applied KMeans and DBSCAN clustering to segment accounts, enhancing marketing engagement efficiency by 50%.

Conducted exploratory data analysis on CRM data using Python to uncover patterns that improved feature selection and data quality. Led data cleaning and NLP with NLTK and SentenceTransformer to extract job title semantics, increasing model accuracy to 90%. Built scalable ML pipelines with XGBoost to impute missing profiling fields across 350K+ records, raising data completeness to 95%. Applied KMeans and DBSCAN clustering to segment accounts for personalized outreach, boosting marketing engagement efficiency by 50%.

Conducted exploratory data analysis (EDA) on CRM data to uncover patterns that improved feature selection and data quality. Orchestrated data cleaning and NLP with NLTK and SentenceTransformer to extract job title semantics, increasing model accuracy to 90%. Built scalable ML pipelines with XGBoost to impute missing profiling fields across 350K+ records, raising data completeness to 95%. Applied KMeans and DBSCAN clustering to segment accounts for personalized outreach, boosting marketing engagement efficiency by 50%.