Hi, I'm Chekitha Swayampu

A Data Professional.

Data Science. Cloud Computing. Machine Learning.
Data Visualization. Database Management.

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ABOUT ME

Hi, I’m Chekitha, a data professional with a sharp eye for detail and a passion for turning complex problems into clear, actionable insights.

I move fluidly between analysis, science, and strategy. Whether it’s uncovering trends in raw data, designing machine learning models, or building dashboards that support real-time decisions, I focus on work that connects data to business outcomes. Over time, I’ve worked across messy supply chains, healthcare data, and operational systems, using Python, SQL, and visualization tools to find the signal in the noise.

I enjoy asking the right questions, working across teams, and using data not just to explain what happened, but to guide what comes next. Always learning, always building because good data should drive smart decisions.

EDUCATION

Vellore Institute of Technology-AP

July 2019 – May 2023

Bachelor of Technology in Computer Science – Data Analysis Specialization
Andhra Pradesh, India

The George Washington University

August 2023 – May 2025

Master of Data Science
Washington, DC

EXPERIENCE

May 2024 – Aug 2024

Data Scientist

ZettaMine Labs Pvt. Ltd. – On-site / Hyderabad, India

• Coordinated a 2-member team to apply NLP-based sentiment analysis on patient surveys and app reviews, identifying negative feedback and dissatisfaction patterns for deeper analysis.
• Developed and optimized a time series forecasting model with 92% accuracy to predict daily bed occupancy across hospital departments, enabling better resource allocation and workforce planning.
• Validated insurance claims and standardized 3M+ clinical records by unifying multi-format data, enabling patient demographic analysis and segmentation for personalized healthcare strategies.
• Collaborated with data engineering and DevOps teams to build and implement ETL pipelines on AWS Redshift and S3, optimizing schema designs.

Jan 2022 – Aug 2023

Data Analyst

Suvega Technologies – Hybrid / Hyderabad, India

• Reduced truck cycle times by 35% by analyzing GPS trip data to improve fleet routing efficiency and delivery speed.
• Identified regional profit trends, visualized 10+ KPIs, and presented insights to managers and non-technical stakeholders.
• Designed and delivered 10+ Tableau dashboards on cargo and vehicle performance using SQL and Python preprocessing, providing real-time insights to support logistics decision-making.
• Resolved delivery location errors by modeling nearest verified drop-off points per zone in GeoPandas, rerouting drivers to proven sites, and lowering erroneous attempts.
• Traced cargo weight discrepancies and used SQL to flag fault trackers and detect missing or incomplete delivery trips.
• Automated incomplete trip and missed delivery reports using SQL and Excel/VBA macros, cutting manual effort by 70%.

Jan 2021 – Dec 2021

SQL Data Analyst

RSSC Solutions – Remote / Chennai, India

• Reduced quality issues by 23% through root cause analysis of defects and inspection logs; detected wear-off patterns and failure durations using trend analysis to enable targeted operational interventions.
• Collaborated with operations managers to collect and organize manufacturing data from disparate sources, building centralized PostgreSQL structures to ensure data integrity and improve reporting.
• Standardized manufacturing data and built Python ETL pipelines, validating 85% of records into PostgreSQL.
• Optimized SQL queries on production and sales data using indexing, reducing query latency, and improving reporting.
• Cleaned and refined SKU datasets by programmatically concatenating image URLs and bulk-downloading 10+ multi-angle product images using Python; implemented a template to automate SKU re-uploads.

SKILLS

Programming & Scripting Languages

Python

SQL

Java

HTML

CSS

Bash

Databases & Storage

MySQL

PostgreSQL

MongoDB

Cassandra

Neo4j

AWS RDS

AWS S3

Big Data & Cloud Technologies

AWS Glue

AWS Lambda

Apache Spark

Microsoft Azure

GCP

Data Analysis & Visualization Tools

Tableau

Power BI

AWS QuickSight

D3.js

PROJECTS

Temperature Forecasting Using ML

Jan 2025 – May 2025 | GWU

A project that applies machine learning, deep learning, and forecasting techniques to predict daily U.S. temperatures, enhanced with feature engineering, visualizations, and interactive dashboards to support climate and environmental decision-making.

Facial Data Evaluation Using CNN

Oct 2022 – Dec 2022 | VIT

A real-time facial analytics system that detects eye and mouth states, age, gender, and emotions using deep learning. Built with MediaPipe’s 468-point Face Mesh, OpenCV, and TensorFlow/Keras, combining landmark ratios with CNN models for multi-feature analysis.

Data Driven Supply Chain Analytics

Sept 2023 – Dec 2023

A complete data mining pipeline for supply chain and sales analysis, combining exploratory data analysis, predictive modeling, and optimization to generate actionable business insights.

Data Brew: Starbucks Customer Segmentation

Aug 2023 – Dec 2023

This project segments Starbucks customers using transaction and offer data. Through preprocessing, feature engineering, and clustering (K-Means), it identifies distinct customer groups, providing insights to personalize marketing, improve engagement, and boost customer retention.

Walmart Sales Forecasting Model

Jan 2024 – May 2024 | GWU

This project focuses on sales forecasting using the M5 Forecasting – Accuracy dataset. It leverages historical sales and external factors such as price, promotions, and events to generate accurate 28-day ahead predictions, supporting improved inventory management and supply chain planning.

Impact of Weather on Energy Consumption

Aug 2024 – Dec 2024 | GWU

Forecasts energy consumption with an AWS SageMaker regression model. An AWS Glue + S3 ETL handles ingestion and feature engineering, and QuickSight dashboards visualize usage and forecasts. Includes data prep scripts, training notebooks, and evaluation metrics.

Deforestation, Carbon & Temperature Trends

Jan 2024 – May 2024

Data-driven story showing how global deforestation raises CO₂ and drives higher temperatures. Interactive Datawrapper visuals integrate multiple datasets into a cohesive narrative. Charts follow visualization best practices: consistent colors, clear font hierarchy, and accessibility-focused design.

Drowsy Driver Alert System

Jan 2022 – June 2022

A real-time drowsiness detection system built with OpenCV, dlib, and deep learning landmarks, designed to enhance driver safety by monitoring fatigue.

Sample Hospital Webpage (HTML/CSS)

Jan 2022 – May 2022

A sample multi-page hospital website for Care & Cure, featuring a home page, doctors directory, and appointment booking. Built with clean HTML and CSS, it demonstrates basic navigation, department links, and responsive design for healthcare websites.