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Hello! I'm a Data Engineer and Data Analyst with experience designing scalable data pipelines, building ETL workflows, and delivering analytics solutions that help organizations make data-driven decisions. I hold a Master's degree in Computer Science from the University of New Haven and have professional experience working with Verizon and other organizations on cloud-based data engineering and business intelligence projects. My expertise includes SQL, Python, AWS, ETL development, data modeling, Power BI, Tableau, and database optimization. I've built automated data pipelines, improved data quality, optimized SQL queries for better performance, and developed interactive dashboards that provide meaningful business insights. I enjoy solving complex data challenges and transforming raw data into reliable, actionable information. What sets me apart is my combination of strong technical skills and business understanding. I focus not only on building efficient data solutions but also on ensuring they deliver measurable value to stakeholders. I'm proactive, detail-oriented, and committed to writing maintainable, scalable solutions while collaborating effectively with cross-functional teams. Whether it's automating workflows, improving data reliability, or supporting business intelligence initiatives, I strive to deliver high-quality results that make an impact.…Hello! I'm a Data Engineer and Data Analyst with experience designing scalable data pipelines, building ETL workflows, and delivering analytics solutions that help organizations make data-driven decisions. I hold a Master's degree in Computer Science from the University of New Haven and have professional experience working with Verizon and other organizations on cloud-based data engineering and business intelligence projects. My expertise includes SQL, Python, AWS, ETL development, data modeling, Power BI, Tableau, and database optimization. I've built automated data pipelines, improved data quality, optimized SQL queries for better performance, and developed interactive dashboards that provide meaningful business insights. I enjoy solving complex data challenges and transforming raw data into reliable, actionable information. What sets me apart is my combination of strong technical skills and business understanding. I focus not only on building efficient data solutions but also on ensuring they deliver measurable value to stakeholders. I'm proactive, detail-oriented, and committed to writing maintainable, scalable solutions while collaborating effectively with cross-functional teams. Whether it's automating workflows, improving data reliability, or supporting business intelligence initiatives, I strive to deliver high-quality results that make an impact.

BHAVANI ODDEPALLI

Data Scientist, AI Developer, AI Prompt Engineer, +2

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Hello! I'm a Data Engineer and Data Analyst with experience designing scalable data pipelines, building ETL workflows, and delivering analytics solutions that help organizations make data-driven decisions. I hold a Master's degree in Computer Science from the University of New Haven and have professional experience working with Verizon and other organizations on cloud-based data engineering and business intelligence projects. My expertise includes SQL, Python, AWS, ETL development, data modeling, Power BI, Tableau, and database optimization. I've built automated data pipelines, improved data quality, optimized SQL queries for better performance, and developed interactive dashboards that provide meaningful business insights. I enjoy solving complex data challenges and transforming raw data into reliable, actionable information. What sets me apart is my combination of strong technical skills and business understanding. I focus not only on building efficient data solutions but also on ensuring they deliver measurable value to stakeholders. I'm proactive, detail-oriented, and committed to writing maintainable, scalable solutions while collaborating effectively with cross-functional teams. Whether it's automating workflows, improving data reliability, or supporting business intelligence initiatives, I strive to deliver high-quality results that make an impact.…Hello! I'm a Data Engineer and Data Analyst with experience designing scalable data pipelines, building ETL workflows, and delivering analytics solutions that help organizations make data-driven decisions. I hold a Master's degree in Computer Science from the University of New Haven and have professional experience working with Verizon and other organizations on cloud-based data engineering and business intelligence projects. My expertise includes SQL, Python, AWS, ETL development, data modeling, Power BI, Tableau, and database optimization. I've built automated data pipelines, improved data quality, optimized SQL queries for better performance, and developed interactive dashboards that provide meaningful business insights. I enjoy solving complex data challenges and transforming raw data into reliable, actionable information. What sets me apart is my combination of strong technical skills and business understanding. I focus not only on building efficient data solutions but also on ensuring they deliver measurable value to stakeholders. I'm proactive, detail-oriented, and committed to writing maintainable, scalable solutions while collaborating effectively with cross-functional teams. Whether it's automating workflows, improving data reliability, or supporting business intelligence initiatives, I strive to deliver high-quality results that make an impact.

Available to hire

Hello! I’m a Data Engineer and Data Analyst with experience designing scalable data pipelines, building ETL workflows, and delivering analytics solutions that help organizations make data-driven decisions. I hold a Master’s degree in Computer Science from the University of New Haven and have professional experience working with Verizon and other organizations on cloud-based data engineering and business intelligence projects.

My expertise includes SQL, Python, AWS, ETL development, data modeling, Power BI, Tableau, and database optimization. I’ve built automated data pipelines, improved data quality, optimized SQL queries for better performance, and developed interactive dashboards that provide meaningful business insights. I enjoy solving complex data challenges and transforming raw data into reliable, actionable information.

What sets me apart is my combination of strong technical skills and business understanding. I focus not only on building efficient data solutions but also on ensuring they deliver measurable value to stakeholders. I’m proactive, detail-oriented, and committed to writing maintainable, scalable solutions while collaborating effectively with cross-functional teams. Whether it’s automating workflows, improving data reliability, or supporting business intelligence initiatives, I strive to deliver high-quality results that make an impact.

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Intermediate

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Work Experience

Data Scientist—Generative AI, LLM & Python Engineering at Verizon

July 1, 2024 - Present

Engineered and deployed a production Python system integrating transformer models and RAG to automate extraction across 10,000+ legal contracts, achieving 92% extraction accuracy and cutting manual review time by 75%. Built and orchestrated LLM-powered automation pipelines using GPT-4 and Claude APIs for clause identification, entity extraction, and document summarization, improving prompt orchestration to reduce error rates by 40%. Developed a codebase-aware semantic retrieval system using FAISS vector embeddings across 500,000+ documents, delivering 89% retrieval precision for automated clause matching. Implemented REST API-integrated real-time analytics dashboards in Python, SQL, and Tableau to monitor extraction accuracy, processing efficiency, and reliability KPIs. Optimized production inference using model quantization and batching strategies in Docker, reducing latency by 60% and achieving sub-2-second response times at scale. Implemented automated data-validation and QA framewo

Data Science Intern at Credit Karma

January 1, 2024 - April 30, 2024

Built and deployed a multi-class document classification system (BERT + XGBoost) processing 50,000+ financial documents daily at 94% accuracy, automating document routing and cutting processing time by 65%. Applied NLP and topic modeling (spaCy, NLTK, LDA) on large-scale customer feedback to generate insights used by product and engineering teams impacting 2M+ users. Engineered automated feature pipelines across MongoDB and PostgreSQL sources, generating 200+ features to support downstream ML models. Validated model reliability via cross-validation, confusion-matrix analysis, and A/B testing prior to production rollout. Built interactive dashboards (Plotly, Seaborn, Tableau) to communicate model performance and findings to non-technical stakeholders.

Junior Data Scientist at Ford Motor Company

March 1, 2022 - July 1, 2023

Built and deployed predictive maintenance models (Random Forest, Gradient Boosting) on telemetry data from 2M+ connected vehicles, achieving 87% accuracy in failure prediction. Automated customer review and warranty-claim analysis using sentiment analysis, named entity recognition, and text classification, cutting manual processing effort by 55%. Conducted large-scale EDA and data mining with Python to uncover patterns driving $2M in cost savings. Built end-to-end production ML pipelines on AWS (SageMaker, Lambda, S3) covering training, evaluation, deployment, and ongoing monitoring. Presented statistical findings and model results to executives and cross-functional engineering teams to support evidence-based decisions.

Data Analyst at Timon Global Pvt Ltd

May 1, 2020 - March 1, 2022

Automated multi-source data collection and processing workflows using Python and SQL, establishing data-quality standards and ETL pipelines. Conducted exploratory data analysis using pandas, matplotlib, and seaborn to surface trends in performance, enrollment, and operations. Designed and optimized SQL queries across MySQL and PostgreSQL databases to support research and administrative reporting systems. Applied regression, correlation, and descriptive statistics to inform strategic planning and research initiatives.