About Me
I'm a client-focused tech professional with 10+ years of experience in operations management, team leadership, sales and client relationship management. Certified in Python (PCEP) and trained in Full Stack software development, I create user-friendly, AI-powered solutions grounded in practical business insights.
I'm comfortable speaking the language of engineers, and equally skilled at translating complex technical concepts into clear, relatable language for non-technical users—helping everyone feel confident and empowered by technology.
My approach combines technical excellence with genuine care for user experience, ensuring my solutions are both impactful and accessible.
Skill Set
Customer Success & Account Management
- Strategic Client Engagement
- Customer Lifecycle Management
- Relationship Building & Retention
- KPI Tracking & Analysis
- NPS & CSAT Management
- CSAT
- Escalation Handling
CRM Tools & Business Systems
- Salesforce (Admin & Lightning)
- Salesforce Chatter
- CRM Administration & Configuration
- BPA & Workflow Optimization
- Systems Integration
- SDLC Methodologies (Agile)
Programming & Analytics
- Python, JavaScript, SQL, HTML/CSS
- RESTful API Development (Flask, Django, FastAPI)
- Responsive Web Design & UI/UX
- CI/CD & DevOps Practices
- Certified Full Stack Developer
- JupyterLab, Pandas, NumPy
- Data Analysis & Process Optimization
- OOP Principles
- Python Certified (Python Institute)
Data Visualization, Reporting & Business Intelligence
- Analytics Dashboards & Custom Dashboards
- Data Visualization Tools (Plotly, Matplotlib, Seaborn)
- BI Reporting & Insights
- Data-Driven Decision Making
- Performance Analysis & Business Systems
AI-Powered Automation
- AI for Business Solutions & Analytics
- LLM Integration (OpenAI GPT, LangChain)
- Model Fine-Tuning & Evaluation
- Generative AI application development (e.g., GPT‑4, Claude)
- Multi-agent systems design with LangChain & agent orchestration tools (Windsurf, Cursor, LangGraph, CrewAI)
- AI pipelines with vector databases & advanced retrieval techniques
- Prompt engineering, evaluation frameworks, & automated testing
Remote Collaboration & Communication
- Client Communication
- Remote Collaboration Tools (Zoom, GitHub, Microsoft Teams)
- Strong Written & Verbal Communication
Business Intelligence & Metrics
- Data-Driven Decision Making
- Performance Analysis & Business Systems
Projects
A sophisticated visual search engine leveraging deep learning to find visually similar images. Built with TensorFlow, Faiss, and Flask, it offers advanced computer vision techniques in an intuitive web interface.
Key Features:
- Visual Similarity Search
- Deep Learning Integration
- High-Performance Vector Search
- Responsive Web Interface
An AI-powered web app that evaluates image aesthetics using TensorFlow's NIMA model based on MobileNet. It provides instant scores with detailed visual feedback for designers and photographers.
Key Features:
- Modern, Intuitive Interface
- AI-Powered Scoring
- Detailed Visual Feedback
- Example Gallery
A dynamic dashboard for trend prediction using time-series data. Built with Flask, statsmodels, scikit-learn, and Plotly, it enables CSV data uploads, interactive visualizations, and performance metric evaluations.
Key Features:
- Advanced Forecasting
- Interactive Visualizations
- Performance Evaluation
- Category-Based Analysis
A predictive model for the 2025 NCAA Basketball Tournament using Python, SQL, Random Forests, and Streamlit to build an end-to-end data pipeline that improved prediction accuracy.
Key Features:
- Data Processing Pipeline
- Feature Engineering
- Model Training
- Prediction Generation
An end-to-end pipeline that extracts structured clinical information from de-identified medical notes using advanced LLMs (OpenAI GPT-4, Anthropic Claude), a FastAPI RESTful API, and robust testing strategies.
Key Features:
- Flexible Data Ingestion
- Dynamic Prompt Engineering
- Comprehensive Validation
- Testing Frameworks
A system that leverages NLP techniques to analyze customer reviews, performing sentiment analysis and visualizing overall trends to help businesses understand client feedback.
Key Features:
- Text Preprocessing
- Multiple ML Models
- Interactive Visualizations
- Streamlit Interface
A robust data pipeline that integrates multiple SaaS APIs (NASA, Dad Jokes, Random User), processes data, and generates synthetic behavioral events for analytics. Built with FastAPI and SQLite, it demonstrates clean architecture, factory pattern implementation, and error handling—ideal for behavioral analytics applications.
Key Features:
- Integrates Multiple SaaS APIs
- Automated Data Processing
- Synthetic Behavioral Event Generation
- Clean Architecture & Error Handling
A neural network for handwritten digit recognition using the MNIST dataset. It demonstrates the use of convolutional neural networks (CNNs) with over 98% accuracy and a simple web interface for real-time predictions.
Key Features:
- CNN Architecture
- Data Augmentation
- Interactive Demo
- Evaluation Metrics
An automated system that generates personalized wellness newsletters by curating content on healthy recipes, workout routines, meditation practices, and wellness tips—powered by NLP to create engaging summaries.
Key Features:
- Content Curation
- Personalization Engine
- Responsive Templates
- Scheduling System
Developed a modular cryptocurrency tracker that fetches real-time data via the CoinGecko API, stores the data in a SQL database, and provides interactive visualizations. This project involves designing an efficient data pipeline, cleaning and managing data with Python, and building dynamic dashboards to monitor market trends.
Key Features:
- Automated Data Collection
- SQL Analytics
- Secure Configuration
- Extensible Architecture