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Bhavani Oddepalli

@bhavanioddepalli

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Senior Data Scientist building production GenAI and ML solutions with RAG, LLM fine-tuning.

United States

Message

What I'm looking for

I’m looking for a role where I can build production GenAI (RAG, LLM fine-tuning) and ML systems that deliver measurable impact—partnering with cross-functional teams and shipping APIs and pipelines in real-world settings.

I’m a Senior Data Scientist with 6 years of experience building and deploying ML and GenAI solutions across healthcare, finance, retail, and supply chain domains. I specialize in LLM fine-tuning and RAG pipeline development, with a focus on production-grade delivery.

At Optum, I architected GenAI-powered LangChain RAG systems that reduced manual review time by 40% and fine-tuned LLMs on FDA/USDA regulatory datasets to cut compliance turnaround from days to hours. I also built real-time GenAI chatbots for factory floor teams, improving SOP adherence by 30%, and delivered customer analytics and margin models that drove $10M in margin recovery.

Earlier, at JPMorgan Chase, I developed supervised ML models reaching 87% accuracy, reducing operational delays by 20%, and identified $250K in savings using statistical methods. I’ve also built ETL pipelines and ML/NLP systems across large-scale datasets at Birlasoft and Accenture, consistently improving reporting efficiency, experiment tracking (MLflow), and data reliability.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Scientist

Current

Optum

Jan 2025 - Present (1 year 6 months)

Architected GenAI-powered LangChain RAG systems to extract structured insights from safety audits and supplier compliance forms, reducing manual review time by 40%. Fine-tuned LLMs and built GenAI chatbots and customer analytics models to improve compliance turnaround, SOP adherence, marketing precision, and margin recovery.

Lang Chain RAG LLM Fine tuning OpenAI API fastAPI Python Vector Databases K Means Decision Trees SVM regression Customer Segmentation

Data Scientist

JPMorgan Chase

Aug 2024 - Dec 2024 (4 months)

Developed supervised ML models to forecast resource demands, achieving 87% accuracy and reducing operational delays by 20%. Delivered analytics improvements through statistical analysis, Tableau dashboards, optimized SQL models, and MLflow experiment tracking.

Random Forest Logistic Regression Python ANOVA Tableau SQL Window Functions MLFlow

Data Scientist

Birlasoft

May 2020 - Jun 2023 (3 years 1 month)

Built predictive models for lead conversions and operational outcomes, improving prediction accuracy by 20%+. Developed NLP pipelines for sentiment analysis and deployed churn prediction models, along with automated reporting and interactive BI dashboards.

XGBoost Random Forest SVM NLTK TF IDF Sentiment Analysis Churn Modeling SQL Alteryx Python Power BI Tableau

Data Engineer

Accenture

Aug 2018 - Jul 2019 (11 months)

Built ETL pipelines using Python, SQL, Apache Spark, and PySpark to process 1B+ records, reducing data load time by 30% and improving throughput by 40%. Developed SQL stored procedures with automated data quality checks and created Tableau dashboards for sales and operational metrics.

Python SQL Apache Spark Pyspark ETL Data Quality Tableau