Divya Gupta

Roles and Responsibilities:

• Defined product roadmaps and translated business requirements into AI/ML-powered solutions, including claim summarization, bid management systems, and QnA Assistants.
• Applied Agentic AI (LangGraph, Crew AI), generative AI frameworks, RAG pipelines, hybrid RAG, self-corrective multi-agents, deep learning (TensorFlow and PyTorch), and CNN to design scalable and robust enterprise solutions.
• Partnered with business stakeholders, engineers, and clients to prioritize features, manage backlogs in Jira, and track delivery through Agile ceremonies.
• Designed KPIs, dashboards, and storytelling sessions to measure product success, and communicate insights to executive leadership.
• Delivered multiple POCs into production, ensuring alignment with client goals, and demonstrating a strong product ownership mindset.
• End-to-end product lifecycle for multiple AI/GenAI initiatives, including claim summarization, bid management systems, and financial chatbots, with cloud deployment.
• Gathered and translated business requirements into clear product roadmaps, user stories, and acceptance criteria.
• Partnered with business leaders, clients, and engineering teams to prioritize features, groom Jira backlogs, and manage sprint planning.
• Defined KPIs, created dashboards, and provided high-level reporting to monitor product performance.
• Stakeholder alignment by facilitating weekly storytelling sessions and collecting feedback loops.
• Delivered POCs and scaled them into production-ready solutions, driving efficiency in healthcare, insurance, and consulting projects. Anticipated key milestones in advance to enhance project timelines.
• Analyzed existing software for optimization opportunities in upcoming releases.
• Identified technical limitations contributing to strategic application optimization.
• Authored maintenance guides for applications to optimize user experience.
• Coordinated quality testing with the assurance team and partnered on resolving defects.

Projects for Health Care:

• Claims Summarization and Question Answering Bot Using Hybrid RAG and Multi-Agents.

Projects for the consulting firm:

• Bid Management System Using Hybrid RAG and Multi-Agents.
• Chatbot assistant for a financial firm.

Projects for Home Insurance:

• Building segmentation, roof segmentation, roof classification, and material detection.

Roles and Responsibilities:

• Requirement gathering to solve the business problem.
• Cleaning of large datasets to provide strategic direction to the project.
• Used Different spatial formats like KMZ and KML.
• Used queries to extract India geographic data and display the data on the map.
• Performing geographic data analysis, data conversion, and data management.
• Designing the Agriculture map using folium, IPyWidgets, Open Layers, QGIS, and leaflet library.
• Designing of different workflows to meet business needs.
• Development and deployment of multiple models by deep learning frameworks and algorithms on premises.
• Developed Proof of Concepts (POC) for agriculture department of India.
• Programming in python to develop a machine learning algorithm and API.
• A/B Testing and Integration testing of different versions of models coded in python.
• Testing and debugging of programs.
• Resolved bugs, improved operations, and provided client support.
• Presentations, documentation, testing, implementation and user support for client reporting.

Projects for Agriculture Department of India:

• Machine Learning (Time Series forecasting) for crops. • Plagiarism Detection using Natural Language Processing. • GIS map creation for Disease Surveillance. • AIML techniques on Plant Pathology & Live stocks.
• Communicated with clients, determining project objectives, gathering data and providing project updates.

• Gathered business requirements by collaborating with teams.
• Conducted research for comprehensive understanding.
• Cleaning Large Datasets: Processed and cleaned data to ensure accuracy and relevance.
• Prepared datasets for strategic project direction.
• Workflow Adaptation: Customized and designed workflows to align with business needs.
• Improved efficiency and effectiveness of processes.
• Deep Learning Model Development: Designed and developed models by using deep learning frameworks like tensorflow, keras and pytorch.
• Utilized GPU machines for improved model performance.
• Proof of Concept (POC) Development: Translated business questions into actionable POCs.
• Demonstrated feasibility and impact of proposed solutions.
• Python Coding for ML and APis: Coded machine learning algorithms and APis in Python.
• Developed solutions for data analysis and integration.
• Unit and Integration Testing: Conducted tests on models for quality assurance.
• Ensured smooth interaction between components.
• Testing and Debugging: Identified and resolved system issues and anomalies.Ensured programmed functionality and stability of solutions.
• Problem Resolution and Client Support: Provided in-house support to address client concerns.
• Enhanced operations and user satisfaction.
• Analysis and Documentation: Analyzed system performance and documented findings.
• Supported knowledge sharing and future reference.
• Platform Transition Support: Assisted in platform transitions, ensuring minimal disruption.
• Provided user support for successful implementation.

Projects for inhouse client:

• License Plate Detection, Recognition (OCR), and Blurring with Single and batch APIs on server-side deployment and Automation.
• Land Cover / Land Use classification for Green Areas, Water Bodies, and Waste land.
• Building footprints detection and Road Footprints (Image classification and Segmentation) through satellite images with REST APIs deployment and Automation.
• Building height measurement by using sun shadow.
• Face Detection, Face blurring with Single and batch APIs on server-side deployment and Automation.

• Requirement Gathering which was analysing extensive datasets using tools like Python.
• R, SAS, and Tableau to gain insights guiding the project's strategic path.
• These insights are translated into valuable risk management strategies.
• Designing for creating customer satisfaction reports through Python-based sentiment analysis and crafting compelling visual narratives using tools like Tableau, Python Libraries and R.
• The identification of opportunities within complex datasets shapes growth-oriented data-driven strategies.
• Developing for the implementation of supervised and unsupervised algorithms, such as Linear/Logistic Regression.
• Time Series Forecasting, and Natural Language Processing (NLP) techniques using Python.
• Coding for using analytical tools such as Python, R, SAS, and Tableau to extract insights from datasets, particularly related to customer sentiment and behavior Algorithms like Linear/Logistic Regression, Clustering, and Decision Trees are also applied Programming further integrates Python, R, SAS, and Tableau to gain strategic insights and create impactful visualizations for business proposals.
• Both supervised and unsupervised algorithms play a role in this phase.
• Debugging was on identifying and resolving programming bugs to enhance system performance, ensuring data accuracy by meticulously compiling and validating data, and presenting structured data solutions to clients.
• Testing of data accuracy, conducts thorough A/B testing and integration testing of various model versions, and enhances program operations by identifying and resolving programming bugs while providing essential client support.

Projects:

• Text Classification, Sentiment Analysis & Text Summarization.
• Credit Card Fraud Detection.
• Loan and Salary prediction.

• Directed academic operations for 14 institutes, leading curriculum planning, admissions, and faculty management.
• Designed and executed large-scale projects (curriculum delivery, admissions cycles, community engagement programs).
• Defined goals, tracked progress, and reported outcomes to senior leadership.
• Supervised cross-functional teams of teachers, telecallers, and coordinators, ensuring smooth program execution.
• Experience here reflects project/program management, stakeholder handling, and team leadership, directly transferable to IT product roles.