Sampath Emandi

Project: AI-Powered Public Grievance Redressal System
Technologies: Python, NLP, Machine Learning, React.js, Flask, PostgreSQL, AppSmith, Selenium, WhatsApp Chatbot, Claude AI, JIRA, Agile

Overview:
Led the development of an AI-driven grievance management system with automated categorization, predictive analytics, and AI-triggered reporting. Integrated a WhatsApp chatbot for seamless user engagement and filing.

Key Responsibilities:

• ML Development: Built NLP models for automatic grievance categorization and predictive analytics for resolution time.
• AI Automation: Automated email triggers and performance reporting, reducing manual effort.
• Chatbot Integration: Developed and deployed a WhatsApp chatbot to improve user adoption and engagement.
• System Architecture: Integrated React.js frontend with Flask backend; designed scalable REST APIs and microservices.
• Data Integration: Scraped data using Selenium and integrated real-time APIs for enhanced model accuracy.
• Agile Project Management: Managed the team using JIRA, ensuring timely delivery of features within sprints.

Project: Multilingual AI Chatbot and Automated Data Extraction
Technologies: Azure, OpenAI GPT, Weaviate, Databricks, ADLS, Streamlit, Plotly Dash, OpenCV, OCR

Overview:
Developed a multilingual AI chatbot and automated data extraction system, leveraging Azure and open-source tools to enhance content retrieval, processing, and visualization.

Key Responsibilities:

• Chatbot Development: Built a multilingual AI chatbot using OpenAI GPT, Azure AI Search, and Weaviate.
• Data Engineering: Developed ETL pipelines with Azure Databricks and Data Factory for scalable data processing.
• AI Optimization: Applied OCR and OpenCV for accurate document processing and extraction.
• User Interface: Designed interactive dashboards with Streamlit and Plotly Dash for real-time updates.
• Automation: Implemented Azure Functions to automate workflows and tracking.

Project: MOA’s UPAG Portal Dashboard and Report Development
Technologies: Plotly Dash, Power BI, SQL, Python, Data Visualization

Overview:
Led the development of interactive dashboards and reports for MOA’s UPAG Portal, centralizing agricultural data to provide actionable insights for decision-making.

Key Responsibilities:

• Dashboard Development: Designed and implemented dashboards using Plotly Dash and Power BI.
• Stakeholder Collaboration: Worked with stakeholders to gather requirements and align visualizations with business needs.
• Data Cleaning & Analysis: Processed agricultural data to extract insights and trends for strategic decision-making.
• Performance Optimization: Continuously improved dashboard performance based on user feedback.

Project: AutoML
Technologies: Python, OOP, Pandas, Scikit-learn, SQL, NoSQL, S3, Machine Learning

Overview:
Developed AutoML to accelerate exploratory data analysis and model development, enhancing machine learning workflows.

Key Responsibilities:

• Data Connectivity & Extraction: Built Python connectors for extracting data from SQL, S3, and other sources.
• Data Preprocessing: Implemented preprocessing pipelines for data cleaning, outlier detection, and normalization.
• Machine Learning Automation: Automated the training, evaluation, and optimization of machine learning models.
• Statistical Testing: Developed modules for performing statistical tests to validate assumptions in linear regression models.

• Managed a portfolio of 300+ high-net-worth clients, utilizing data analytics to optimize client acquisition, retention, and investment strategies, resulting in a 20% increase in client engagement
• Employed Python and SQL to develop predictive models for identifying upselling and cross-selling opportunities, boosting targeted prospecting efficiency by 35%
• Delivered strategic presentations using data insights to influence senior management’s decisions on wealth products, driving a 10% increase in market share
• Applied advanced segmentation techniques to personalize wealth management solutions, leading to a 25% improvement in product conversions
• Partnered with sales teams to translate data into actionable client strategies, contributing to 15% growth in new product adoption

• Managed a portfolio of over 250 clients, leveraging data science insights to drive client acquisition and retention strategies
• Developed and delivered strategic data presentations to senior management, influencing business decisions on cross-selling and upselling opportunities
• Utilized Python for predictive analysis and client segmentation, increasing targeted prospecting efficiency by 30%
• Collaborated with sales teams to translate client needs into actionable solutions, driving business growth and improving client satisfaction