Data Analyst / Associate

LAKSHMI MOUNIKA BOLISETTI

Indianapolis, Indiana (Open to relocation) +1-317-***-**** ********@*****.*** LinkedIn GitHub Results-driven Data and AI Specialist with 4+ years of experience leading cross-functional technical projects, building AI-driven tools, and delivering scalable data products. Adept at using NLP, LLMs, SQL, and visualization to support product development, streamline workflows, and enhance end-user experiences.

EXPERIENCE

Indiana University Client Data Analyst Jul 2024 - Present

• Generated weekly, monthly, and ad-hoc analytical reports for the university library's event management and public service operations, enabling data-informed decision-making across teams.

• Conducted statistical analysis and visualized customer feedback and operational data using Python and visualization tools, identifying trends and inefficiencies that led to a 20% improvement in service efficiency.

• Collaborated with cross-functional stakeholders to translate insights into actionable recommendations and data-driven initiatives, enhanc- ing workflows and refining user experience strategies through data storytelling and stakeholder communication. Indiana University Research Data Scientist III Oct 2023 - Present

• Built an intent-based chatbot for the Indianapolis Public Library using BERT Transformers, Hugging Face, and NLP tools at the same time used Selenium for web scraping and JSON scripting.

• Developed a responsive Flask frontend with HTML, CSS, and JavaScript -- boosting user engagement by 60%.

• Collected and analyzed user interaction data from the SAVI website to understand platform workflows and user behavior.

• Proposed and implemented AI-embedded solutions to enhance user experience and improve overall website efficiency.

• Fine-tuned a LLM model for the SAVI website using LLaMA, LangChain, API key integration, NLP, and prompt engineering.

• Vectorized the database and optimized ETL pipelines for structured querying.

• Developed a text-to-SQL model and performed unit testing, functional testing, and UAT testing, achieving 83% execution accuracy.

• Currently building a small custom language model for the SAVI platform chatbot. Leveraging Selenium and BeautifulSoup for data collection and web scraping, and using NLP tools and BERT Transformers for generating data-driven responses. Capgemini Technology Services Senior Software Engineer Aug 2021 - Jul 2023

• Led a proof of concept (PoC) to establish a multi-platform VPN connection across AWS, Azure, and GCP using Terraform and cloud consoles. Implemented and monitored secure ETL pipelines and performance KPIs, reducing deployment errors by 30%.

• Collaborated with cross-functional teams to troubleshoot integration issues and execute ad-hoc scripts for version upgrades of Guidewire Claims software, leveraging KPIs and SQL to enhance CI/CD pipeline stability by 45% while ensuring data governance and compliance.

• Engineered a disaster recovery solution for an insurance provider by developing a secondary AWS-hosted website for Guidewire Claims services. Maintained CI/CD of ETL pipelines while supporting uptime and reducing risk of data loss.

• Developed and maintained 50+ automation scripts using Java, Selenium, and Cucumber BDD for data validation, web scraping, and testing.

• Executed UAT, regression, functional, and unit testing—achieving a 55% reduction in data inconsistencies and improving processing efficiency. Documented workflows and strategies to support Agile/Scrum-based delivery and knowledge transfer. EDUCATION

Indiana University Aug 2023 - Present

Master of Science, Applied Data Science (GPA: 3.97/4.0) Indianapolis, Indiana, USA VNR Vignana Jyothi Institute of Engineering and Technology Jun 2017 - Jul 2021 Bachelor of Technology, Mechanical Engineering (GPA: 9.43/10)

• Achievements: Gold medalist (Best Outgoing Student of the year 2021) Hyderabad, Telangana, India

TECHNICAL SKILLS

• Languages: Python, C/C++, SQL, XML, HTML, CSS, R, PHP, SAS, Microsoft Access, Linux/Unix

• Applications/Tools: VS Code, Streamlit, Pandas, Matplotlib, Seaborn, Tableau, Microsoft Power BI, Git, DevOps, Keras, TensorFlow, CNN, MATLAB, Kubernetes, Docker, Terraform, ArcGIS, Hazus, ShakeMap, AutoCAD, Ansys

• Microsoft Tools: Microsoft Excel (Pivot Tables, VLOOKUP, VBA, and Advanced Excel), Microsoft Word, Microsoft PowerPoint, Microsoft 365, Microsoft Suite, Microsoft Access

• Databases/Cloud: MySQL, MongoDB, Google Cloud Platform (GCP), Microsoft Azure, Amazon Web Services (AWS)

• Skills: Data analysis, Data Visualization, Machine learning, Cloud Computing, GIS, Deep learning, Artificial Intelligence, Project Management, Communication Skills, Statistics, Test Automation, Databricks, RAG PROJECTS

Symptom Based Disease Prediction

• Built an AI-powered chatbot using FNN, ANN, LSTM, and combination models to analyze complex clinical datasets (symptoms and patient histories), achieving 86.89% accuracy in medical diagnosis and preventive care suggestions.

• Performed exploratory data analysis (EDA), applied fuzzy matching, and created Python-based visualizations using Keras and Scikit-learn to improve interpretability of large-scale, heterogeneous medical data for clinicians. Medical Insurance Fraud Detection Model

• Implemented a scalable fraud detection ML model using Apache Spark and Random Forest, achieving 94.21% training accuracy on medical insurance claims data. Optimized feature engineering and preprocessing workflows in Python for cloud-ready deployment.

• Maintained high-quality data pipelines to ensure efficient data processing, enhancing fraud detection performance and preserving data integrity across the analytics lifecycle.

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