Open to opportunities

Chandra Teja Kokkonda

@chandratejakokkonda

Message

AI/ML engineer turning data into forecasting and RAG chatbot solutions that deliver measurable business impact.

United States

Message

What I'm looking for

I’m looking for a role where I can build end-to-end AI/ML products—forecasting, RAG chatbots, and analytics dashboards—while collaborating with teams that value measurable outcomes, clean engineering, and responsible AI.

I’m an AI/ML engineer focused on building practical, production-minded machine learning and generative AI systems—especially time-series forecasting, data visualization, and RAG-based chatbots. I translate raw data into actionable insights, whether I’m engineering risk models for healthcare scenarios or optimizing retrieval and prompting pipelines to improve answer quality and efficiency.

In my recent work, I built an alerting API for budget overruns and overwork forecasts that reduced unexpected costs by 20% and improved workload balance by 15%. I also developed an MCP server and an AI-powered Slackbot that cut software-switching time by 30% and increased creative team efficiency by 25%, while saving 10+ hours weekly. Alongside this, I built ML models achieving 88% accuracy for disease risk prediction, and deployed a Flask app that combined a hospital finder with a responsive UI—making the tool accessible for non-technical users.

Experience

Work history, roles, and key accomplishments

Prompt Engineer Intern

Paradowski Creative

Jun 2025 - Jul 2025 (1 month)

Built an API for automated budget-overrun alerts and overwork forecasts, reducing unexpected costs by 20% and improving workload balance by 15%. Developed an MCP server and Slackbot to streamline project/team management with AI, cutting software-switching time by 30% and improving creative efficiency by 25%.

Prompt Engineering Agentic AI Generative AI Automated Alert APIs Forecasting Slackbot Development Text To Speech Image To Video Storyboarding

Data Analyst Intern

Saint Louis University

Jan 2025 - May 2025 (4 months)

Developed statistical ML models (Random Forest, scikit-learn) to predict CKD, diabetes, and heart disease risk, achieving 88% accuracy to improve early-stage risk identification. Performed data preprocessing and feature engineering with Pandas and NumPy, improving data quality by 40%, and deployed a Flask web app that integrated a hospital finder for non-technical users.

Random Forest scikit learn Statistical Modeling Pandas NumPy Feature Engineering data preprocessing Flask Deployment

Education

Degrees, certifications, and relevant coursework

Saint Louis University

Master of Science, Computer and Information Sciences

2023 - 2025

Grade: GPA: 3.72 / 4.0

Activities and societies: Research Project: Health Predict—AI Power Disease Risk Assessment & Hospital Locator. Coursework: Software Development; Manage a Secure Enterprise; Mobile & Web Application Development; Data Analysis.

Earned an M.S. in Computer and Information Sciences (2023–2025). Conducted research for Health Predict: AI Power Disease Risk Assessment & Hospital Locator and completed related software and data coursework.