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KANAKANTI HEMANTH KUMAR REDDY

Data Analyst • Anapagutta, Madanapalle - 517325 • h***************@gmail.com • 901****177 • drivetube.ai/•••••

Professional Summary

Data Analyst with 0 years of experience specializing in Excel, SQL, Python, and Power BI. Skilled in data cleaning, validation, automation, and dashboarding to deliver accurate business reporting and actionable insights. Experienced in end-to-end data workflows, visualization, and applying statistical methods such as PCA and time-series analysis to support data-driven decisions.

Technical Skills

Programming Languages: Python
Web Technologies: REST APIs
Frameworks and Libraries: Pandas,NumPy,Matplotlib,Seaborn,Node.js
Databases: SQL,Relational Databases
Data and Analytics: Power BI,Excel,Data Cleaning,Data Validation,Data Preprocessing,Automation of Data Workflows
Tools and Methodologies: MS Excel,SPSS,EViews,Agile,Version Control Concepts
Statistical and Econometric Methods: Principal Component Analysis PCA,Time-Series Analysis,ARDL,Cointegration,Causality Testing
Reporting and UX: Dashboard Design,UI,UX Improvements

Work Experience

KPIT Technologies
Management Trainee Intern
Jun 2026 – Jul 2026
Worked at an IT engineering and services company supporting HR analytics and workforce reporting through attendance and attrition analysis.
Tech Stack: MS Excel, Power BI
  • Analyzed employee attendance datasets in Excel to identify patterns and trends, consolidating multiple attendance sources into a clean reporting table for HR stakeholders.
  • Built interactive Power BI reports to visualize attendance trends and attrition drivers, enabling HR to identify high-risk groups and seasonal patterns.
  • Performed attrition analysis using Power BI and Excel, segmenting workforce by tenure and department to surface actionable retention opportunities.
  • Conducted SWOT analysis combining quantitative HR findings and qualitative research to inform recommendations shared with senior HR and team leads.
  • Automated repetitive Excel tasks with structured templates and formulas to improve report turnaround time and reduce manual errors in monthly dashboards.
  • Prepared presentations summarizing analytical findings and presented insights to cross-functional teams, improving visibility of workforce metrics for decision making.
Infosys Springboard
Data Visualisation Intern
Feb 2026 – Apr 2026
Participated in a training/program initiative building an AI-powered cyber threat visualization dashboard; responsible for data ingestion, cleaning, and dashboard delivery.
Tech Stack: Python, SQL, Node.js, Power BI, REST APIs, Agile
  • Collected and ingested real-time cyber threat data via APIs using Python, implementing retrieval and scheduling workflows to maintain up-to-date datasets.
  • Developed Python-based data cleaning and preprocessing pipelines (missing-value handling, normalization) to ensure high-quality input for visualization and AI modules.
  • Extracted and transformed structured threat data with SQL queries to produce analysis-ready tables for dashboard metrics and trend analysis.
  • Integrated AI-driven insights into the visualization pipeline to highlight anomalous events and threat patterns for SOC-style monitoring use cases.
  • Contributed UI/UX improvements to the dashboard to simplify interpretation of complex threat indicators and enhance user navigation for analysts.
  • Followed Agile practices within the project team, participating in sprint planning, demos, and iterative feedback cycles to deliver a scalable interactive dashboard.

Projects

Interactive Cyber Threat Visualization Dashboard
Tools Used: Python, SQL, Node.js, Power BI, REST APIs, Data Cleaning
  • Developed end-to-end data pipelines to collect, clean, and aggregate cyber threat feeds for near-real-time visualization.
  • Automated data processing workflows with Python and SQL to reduce manual preparation and support continuous dashboard refreshes.
  • Implemented backend components using Node.js to enable dynamic data handling and deliver timely metrics to the frontend visualization.
  • Designed dashboard UI/UX and visualizations to present threat severity, frequency, and source trends for analyst consumption.
Digital Payments and Economic Growth in India – Empirical Analysis
Tools Used: Python, Excel, EViews, Power BI, PCA, Time-Series Analysis
  • Constructed a Digital Payment Volume Index (DPI) using Principal Component Analysis to measure adoption trends across multiple indicators.
  • Performed time-series econometric analysis (ARDL, cointegration, causality tests) to evaluate relationships between digital payments and GDP.
  • Automated data processing and statistical workflows with Python and Excel to improve reproducibility and analysis accuracy.
  • Created an interactive Power BI dashboard to visualize macroeconomic trends, correlations, and model results for stakeholders.

Education

Madanapalle Institute of Technology and Science
Master of Business Administration in Analytics and Finance • June 2026
Shri Gnanambica Degree College
Bachelors in Commerce and Computer Applications • July 2024
Sri Siddhartha Junior College
Intermediate - Commerce Economics and Civics • May 2021
Bharath E.M High School
Secondary School Certificate • May 2019

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