Punam Naik

Spearheaded development of GenAi applications leveraging GPT-powered large language models (LLMs), such as chatbots for Field Service Assistant, Ticket Classification, and Asset Performance Management in the Oil and Gas industry. Implemented embeddings on diverse data formats including PDFs, CSVs, and text, enhancing GenAi RAG applications using frameworks like Hugging Face and OpenAI. Explored various chains and agents within the LangChain framework using Python, optimizing workflows for AI-driven applications. Applied advanced data analytics skills to extract actionable insights through Kibana, OpenSearch, and Power BI dashboards for CCC, a web-based platform enabling real-time monitoring and control of business units within the Oil and Gas sector.

Collaborated closely with the UI team to integrate Elasticsearch and JWT into APIs, ensuring scalable solutions that met business requirements. Managed data operations proficiently by executing a variety of elastic operations within the ELK stack. Developed advanced queries and utilized Python scripts for REST API operations with Elasticsearch and OpenSearch. Automated daily tasks through the creation of bash scripts and Linux services, significantly enhancing operational efficiency and workflow automation. Designed and implemented object detection models for safety applications in the energy sector, including detection of safety helmets, eyeglasses, protective jackets, fire and smoke, and critical area monitoring through video analytics. Developed a functional chatbot using the RASA framework, integrating CRUD database operations to enhance its capabilities.

Conducted comprehensive data analysis, including Error Trend and Aging Analysis, utilizing Excel and Power BI. Expertly extracted data through JQL queries and produced regular error reports, driving actionable insights to mitigate errors and enhance operational performance. Designed and implemented an interactive Project Dashboard leveraging Atlassian tools such as Confluence and Jira. Monitored key performance indicators (KPIs) across all users, providing real-time visibility and facilitating informed decision-making. Mentored team members through facilitated discussions and brainstorming sessions with the production team, resulting in enhanced quality standards and a reduction in errors. Researched object classification utilizing the VGG-16 model, and implemented the random forest algorithm for proof-of-concept (POC) development.

Designed high-definition route plans using specialized tools for geo-spatial data, aimed at optimizing navigation for autonomous vehicles. Generated periodic progress and error reports, and conducted data analysis using Confluence and Jira tools, facilitating informed decision-making and continuous improvement.