Data analyst/Engineer

NITISH KUMAR GUDDETI

***********@*****.*** +1-562-***-**** West Covina, CA LinkedIn

EDUCATION

• Master’s in Business Analytics Aug 2023 – Aug 2025 Cal Poly Pomona, California.

• Bachelor’s in Biomedical Engineering May 2020

B. V. Raju Institute of Technology

SKILLS

Data Visualization & Data Engineering: Power BI, Tableau, Big Data, Hadoop, PySpark, Spark, Vector Search, Embedding Models Technologies: Machine Learning, Natural Language Processing, Deep Learning, Artificial Intelligence, Retrieval-Augmented Generation

(RAG), GenAI, Semantic Search

Cloud Technologies: Azure Data Factory, Azure Databricks, ADLS, Azure ML Studio Programming Languages & Databases: Python, Java, R, Oracle, MySQL, SQL, PostgreSQL Libraries: NumPy, Pandas, Matplotlib, Seaborn, BeautifulSoup, Scikit-Learn, PyTorch, Keras, TensorFlow, NLTK, SpaCy, FAISS, Scipy Tools & Others: Quip, Jupyter Notebook, Google Colab, Excel, Git, Eclipse, Postman, JIRA, Soap UI, Streamlit, Databricks Genie, MS Office Suite (Word, Excel, PowerPoint, Outlook), Agile Methodologies WORK EXPERIENCE

SPECIALIST PROGRAMMER /DATA ENGINEER, INFOSYS Hyderabad, India Sep 2021 - Aug 2023

• Architected high-performance data pipelines in Azure Data Factory that processed 250+ million records daily with 35% faster execution

• Spearheaded implementation of Databricks ML-powered transformations, elevating data quality metrics by 40% across enterprise systems

• Developed advanced business analytics solutions that transformed raw financial data into actionable intelligence, improving decision-making efficiency

• Engineered mission-critical Azure Logic Apps that automated 80% of business processes, reducing operational costs significantly

• Followed all company policies and procedures to deliver quality work.

• Improved customer satisfaction rates through proactive problem-solving and efficient complaint resolution.

• Revolutionized reporting framework with Power BI Paginated Reports, decreasing generation time from 4 hours to 45 minutes

• Collaborated with cross-functional teams to achieve project goals on time and within budget.

• Led development of ADF pipelines for Anti-Money Laundering (ODR module) compliance, identifying 28% more suspicious transactions while reducing false positives by 15%

• Implemented new training programs for staff, leading to higher employee retention rates and better overall performance.

• Optimized international ACH transaction processing with advanced data flows, handling 25% higher volume with accuracy and 42% faster settlement

• Implemented real-time data enrichment with Azure Functions, cutting processing latency by 42% and improving data completeness by 37%

• Leveraged Databricks for complex data transformations and feature engineering, enhancing AML model accuracy by 31%

• Collaborated with cross-functional teams including BI analysts and Reporting teams to streamline data delivery pipelines, resulting in 30% faster insights generation

• Conducted comprehensive competitor analysis to inform strategic decisions. DIGITAL SPECIALIST ENGINEER, INFOSYS Pune, India

Sep 2020 -Aug 2021

• Designed and maintained enterprise data warehousing solutions using SSIS, SQL Server, and Oracle, achieving 45% improvement in query performance

• Delivered cutting-edge OCR solution using Azure Databricks and PySpark, achieving 22% higher accuracy and processing 15,000+ documents daily

• Pioneered cloud migration strategy that transferred 18TB of on-premises data to Azure SQL, reducing infrastructure costs by 38% and boosting query performance by 27%

• Transformed HR analytics through Python-powered predictive models, identifying retention factors that decreased turnover by 15%

• Designed executive-level Power BI dashboards (R&R Analytics) that revealed actionable customer insights, directly contributing to 12% revenue growth

• Implemented end-to-end ETL processes for business analytics platforms, supporting data-driven decision making across 5 major business units

• Resolved critical Power BI Gateway issues within SLA, increasing system reliability from 85% to 99.5% uptime across 12 production environments

• Engineered enterprise-grade ETL frameworks with SSIS that accelerated data warehouse loads by 40% while maintaining 100% data integrity

• Implemented sophisticated Row-Level Security protocols that ensured regulatory compliance while reducing report generation overhead by 33%

• Executed multiple successful projects including Team Optimization, Monthly Incidents, Risk Incidents, DRC-IT, Migration, TRMLogic, and Score Card projects

• Created data models and relationships between tables in Power BI, improving report performance by 28%

• Developed new functionalities and RESTful web APIs using Spring Boot and Hibernate frameworks, including features like adding a set of bookings as favorites and a search field for efficiently searching and filtering bookings

• Assisted clients in gathering test data for different scenarios to validate against business rules, enhancing the shipment tracking service's robustness and readiness for release

PROJECTS

AI-Powered Community Insights: Integrating LLMs and Location Analytics for Solar Energy This research harnesses Large Language Models (LLMs) and computational sentiment analysis to extract actionable insights from unstructured county-level meeting transcripts, quantifying stakeholder perspectives and regulatory frameworks affecting solar PV development. The methodology combines LLM-driven text analytics with geospatial data to identify jurisdiction-specific sentiment patterns and compliance requirements, creating a multidimensional framework that optimizes site selection parameters and mitigates community opposition within the rapidly expanding solar market. AI-Driven Claims Verification System Databricks Hackathon 2025 Built an intelligent healthcare claims processing pipeline using Retrieval-Augmented Generation (RAG) and GenAI on Databricks. Integrated structured insurance data with unstructured medical transcriptions using vector embeddings and natural language QA. Enabled real-time claim validation, fraud detection, and insights via Databricks Dashboards and Genie. Delivered a scalable, explainable solution aligned with HIPAA standards, reducing claim denials and optimizing billing accuracy. AI in the Headlines: Unveiling Media Trends and Sentiments on CNN and BBC Analyzed AI-related headlines and leads from CNN and BBC using LDA topic modeling, uncovering media trends and sentiments with detailed visualizations. The project revealed significant differences in AI portrayal, with CNN presenting AI more positively and BBC offering a broader, slightly more critical perspective. These insights underscore the importance of diverse media sources in shaping public perception and policy discussions on AI.

Data Modeling & Data Warehouse

Designed and implemented a data warehouse for retail inventory and sales using SSMS, SSIS, and Power BI. Created an ER data model and performed ETL processes to support data analysis and decision-making. Drip-M

Led a team in developing Drip.M, a hardware device for controlling and monitoring IV flow in hospitals using Flutter, Firebase, Arduino, and Fusion360, achieving recognition at BioAsia 2020, GE Hack’E’lth 2019 (1st prize), and Startup India Yatra 2018 (top 100 finalist). ACHIEVEMENTS

• Selected and represented Drip M project in BioAsia 2020

• Won first prize in GE Hack'E'lth 2019

• One of the 100 Finalists in Startup India Yatra 2018

• Won Concession prize in 'Anveshana 2019

• Concession prize in 'Smart India Hackathon 2019- Hardware Edition'

• Organized National Level Technical Symposium 'PROMETHEAN 2019' CERTIFICATIONS

• Infosys Certified Python Associate & Full Stack Developer Java Spring and Angular

• Microsoft Certified Cloud Practitioner: AZ-900, DP-900

Contact this candidate