Hi, I'm Bhupendra

Leading enterprise-level graph database implementations and mentoring development teams. Spearheading innovative solutions that process millions of data relationships daily.

• Architected graph-based recommendation systems serving 2M+ users
• Optimized database performance by 60% through query optimization
• Mentored 15+ junior developers in Neo4j best practices
• Implemented real-time fraud detection saving $2M annually
• Developed and automated SCADA data integration into Neo4j by building Python-based ETL pipelines, reducing processing time by 90% and standardizing data workflows. Applied advanced graph data modeling and Cypher query optimization to enhance smart grid analytics, integrated multiple data sources for real-time and batch ingestion, and improved network visualization through Neo4j Bloom. Delivered high-accuracy data validation mechanisms and provided documentation and training to engineering teams, enabling faster, more reliable decision-making.

Designed and implemented machine learning models for predictive analytics, performing data preprocessing, feature engineering, and model evaluation to improve accuracy. Developed Python-based pipelines for data collection, cleaning, and visualization, and applied algorithms for classification, regression, and clustering tasks.

• Collaborated with senior data scientists to fine-tune models, automate workflows, and document methodologies
• Contributed to faster and more reliable deployment of AI solutions
• Performed comprehensive data preprocessing, feature engineering, and model evaluation
• Applied algorithms for classification, regression, and clustering tasks