Sai Varsha

AI Engineer •Building Intelligent AI & Data Systems That Drive Real Business Impact

SAI VARSHA SREEPERUMBUDUR

AI Engineer with a Master’s degree in Data Science (University of Nebraska at Omaha), specializing in scalable, production-ready AI and ML systems that transform enterprise data into intelligent, decision-driven platforms.

LLM Workflows Vector Databases Data Pipelines Forecasting AWS Python & SQL TypeScript Power BI
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Sai Varsha Profile Photo

Highlights

  • Build end-to-end AI workflows integrating LLMs, vector DBs, APIs, and automation.
  • Design ETL/ELT pipelines with validation, quality checks, and production monitoring.
  • Deliver dashboards and decision support for business stakeholders.
  • Build React + TypeScript dashboard components and BI reporting workflows.
  • Deploy cloud-ready solutions (AWS) with reliability and secure data handling.
AI
Systems Focus
Location
Nebraska

About

I am an AI Engineer specialising in building scalable AI and machine learning systems. My work focuses on designing production-ready solutions that integrate LLMs, vector databases, and automated data pipelines to transform enterprise data into intelligent, decision-driven systems.

I have experience developing end-to-end ML pipelines, engineering ETL/ELT workflows, orchestrating AI processes, and deploying solutions in cloud environments using Python, SQL, and AWS. My software development background helps me bridge data engineering, machine learning, and application development to deliver secure and high-performance AI platforms.

Education

  • M.S. Data Science (IT Concentration) — University of Nebraska at Omaha (Jan 2024 – Dec 2025)
  • B.Tech Electrical & Electronics Engineering — Vardhaman College of Engineering (2019 – 2023)

Core Competencies

AI Engineering LLM Integration Vector Databases ETL/ELT Pipelines Python + SQL AWS React TypeScript Power BI (DAX) Data Modeling Forecasting Dashboards

Experience

AI Engineer Hustad Companies Inc • Jun 2025 – Present
  • Designed and maintained automated data pipelines using Python, SQL, and REST APIs to ingest, transform, and load data from enterprise systems.
  • Orchestrated AI workflows integrating LLMs, vector databases, REST APIs, and automation to deliver end-user solutions.
  • Supported production reliability: debugged pipeline failures and optimized query + pipeline performance.
  • Built React + TypeScript UI components and API-driven state management for real-time operational dashboards.
  • Delivered BI reporting workflows and dashboards for stakeholders; enforced secure access-controlled integrations.
Graduate Data Science & Analytics Assistant University of Nebraska at Omaha • Feb 2024 – May 2025
  • Performed applied analysis and ML on large structured datasets using Python, SQL, and R (EDA, cleaning, feature engineering).
  • Built and evaluated regression/classification/time-series models to support data-driven decision-making.
  • Developed repeatable dashboards in Power BI and Tableau for insight delivery.
  • Communicated findings to technical and non-technical stakeholders with actionable recommendations.
Software Developer CGI • Jun 2022 – Dec 2023
  • Developed backend data loads and integrations using SQL Server (MSSQL) in a .NET enterprise environment.
  • Automated ETL processes and data workflows to improve reliability and performance.
  • Worked in Agile teams delivering production-ready solutions with scalability and data quality focus.

Portfolio

Child Care Staffing Forecasting & Scheduling

Forecast workforce demand using time-series modeling and machine learning to support data-driven staffing decisions.

  • Built an end-to-end pipeline transforming attendance events into structured time-series datasets.
  • Compared GAM, Random Forest, and PyTorch models using backtesting and consistent evaluation metrics.
  • Delivered interactive reporting and decision-support insights for operational planning.
Python SQL PyTorch AWS Power BI Forecasting
🎥 YouTube Walkthrough

Sales Analytics & BI Dashboards

Business intelligence dashboards for performance tracking using scalable star-schema data modeling.

Sales Analytics Dashboard Screenshot
  • Designed analytics-ready relational datasets using SQL transformations.
  • Built optimized Power BI semantic models with DAX measures.
  • Improved performance and enabled repeatable self-service reporting.
Power BI DAX SQL Star Schema Data Modeling

Customer Churn Prediction & Predictive Analytics

Built supervised learning models to identify churn-driving patterns and improve customer retention strategy.

  • Performed exploratory data analysis and feature engineering.
  • Trained Logistic Regression and Random Forest models.
  • Evaluated performance using ROC-AUC, Precision, Recall, and F1-score.
Python SQL Scikit-learn Classification Model Evaluation

US Labor Statistics Explorer

Interactive Streamlit application for exploring U.S. labor market indicators with clean visual insights.

  • Built a structured analytics pipeline to process labor market datasets.
  • Designed interactive visualizations for trend exploration and comparison.
  • Focused on reproducible analytics and user-friendly dashboards.
Python Streamlit Data Visualization
💻 GitHub Repo 🚀 Live App

Publications & Achievements

IEEE Publication

Published a research paper in IEEE. Available on IEEE Xplore Digital Library.

View on IEEE Xplore

🏆 FNBO Datathon 2024 — 2nd Place

Secured second place by analyzing customer reward programs to uncover spending patterns, engagement trends, and loyalty insights. Built ML models and Power BI dashboards delivering actionable business recommendations.

FNBO Datathon Certificate FNBO Datathon Group Photo

Services

BI Engineering (Power BI · Fabric)

Built Power BI solutions end-to-end — from data ingestion to semantic modeling and executive-ready dashboards.

  • Designed semantic models and reusable DAX measures.
  • Worked with Microsoft Fabric (Lakehouse, model layer, reporting).
  • Connected APIs & enterprise sources for refreshable dataflows.
  • Built drill-through dashboards with performance tuning.

Data Engineering (ETL/ELT)

Reliable ingestion, validation, and transformation pipelines for production analytics.

  • Automated pipelines using Python + SQL.
  • Implemented monitoring & data quality checks.
  • Built analytics-ready datasets for BI & ML.

AI Workflow Automation (LLM Systems)

Designed AI systems that automate workflows while ensuring control and reliability.

  • Defined structured agent workflows.
  • Implemented human-in-the-loop validation.
  • Applied guardrails for safe automation.

Predictive Analytics & Forecasting

Time-series forecasting and predictive modeling aligned with business outcomes.

  • Built backtested forecasting pipelines.
  • Translated predictions into executive dashboards.

Contact

Feel free to reach out for AI engineering opportunities, collaboration, or consulting.

LocationNebraska

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