Skip to content

Yogitha Devarapally

Associate Data Analyst • United States • y*********************@gmail.com • 609****564

Professional Summary

Associate Data Analyst with 2+ years of experience delivering ETL workflows, SQL analytics, dashboarding, and automated reporting to support business decisions. Experienced with Python (Pandas, NumPy), SQL, Power BI, Tableau, Excel, and statistical tools (SAS, SPSS). Skilled at converting raw data into validated KPIs and interactive dashboards consumed by business stakeholders.

Technical Skills

Programming Languages: Python,Java
Web Technologies: REST APIs
Frameworks and Libraries: Pandas,NumPy,scikit-learn,Matplotlib,Seaborn,TensorFlow
Databases: SQL,MySQL,PostgreSQL
Data and Analytics: Classification Models,Feature Engineering,Power BI,Tableau,Microsoft Excel,Power Pivot,SAS,SPSS,Statistical Analysis,Predictive Analytics,ETL,Data Cleaning,Data Validation,Reporting Automation
Tools and Methodologies: Jupyter Notebook,Git,VS Code
Concepts & Methods: Data Modeling,Data Quality,KPI Reporting,Dashboard Development

Work Experience

Amsoft Corp
Dayton, NJ
Associate Data Analyst
Mar 2025 – Present
Provided data analysis, ETL and dashboarding to support cross-functional business stakeholders and reporting workflows.
Tech Stack: Python, Pandas, NumPy, SQL, Power BI, Tableau, Microsoft Excel, Jupyter Notebook, Git
  • Partnered with cross-functional stakeholders to gather analytic requirements and translate business questions into repeatable data models and dashboards using Power BI and SQL.
  • Engineered reusable ETL pipelines in Python (Pandas) to extract and transform data from operational sources for reporting, improving data preparation consistency across reports.
  • Performed exploratory data analysis to discover trends and anomalies, producing insights used in weekly stakeholder reviews and decision-making.
  • Built interactive KPI dashboards in Power BI and Tableau that centralized key operational metrics and reduced time-to-insight for business users.
  • Authored complex SQL queries to join, aggregate, and filter relational datasets for ad-hoc analysis and scheduled reporting delivered to business teams.
  • Automated recurring reporting tasks and validation checks with Python and SQL to reduce manual effort and ensure consistent data quality in production reports.
Southernindia Pvt. Ltd.
Hyderabad, India
Junior Data Analyst
Jan 2022 – Oct 2022
Delivered analytics, dashboards, and statistical reporting to business teams using SQL, Python and BI tools to support operational and forecasting needs.
Tech Stack: SQL, Python, Microsoft Excel, Power BI, SAS, SPSS, Tableau
  • Analyzed structured and unstructured datasets using SQL and Python to identify patterns and operational trends supporting business reporting.
  • Designed and maintained Power BI and Excel dashboards to monitor KPIs and share actionable insights with technical and non-technical stakeholders.
  • Cleaned and transformed raw data—handling missing values and outliers—using Python and Excel to improve downstream reporting accuracy.
  • Wrote optimized SQL queries to retrieve, join and aggregate data from multiple sources for recurring reports and ad-hoc analyses.
  • Automated routine data preparation and reporting processes to improve operational efficiency and reduce manual processing time.
  • Conducted statistical analyses with SAS and SPSS to support forecasting and performance measurement communicated via reports and presentations.

Projects

Emotion Detection Using EEG Signals
Tools Used: Python, Pandas, NumPy, TensorFlow, Matplotlib
  • Processed EEG time-series data applying noise reduction and signal preprocessing routines to improve model input quality.
  • Engineered time-series features using NumPy and Pandas to capture temporal patterns relevant to emotion states.
  • Trained and evaluated deep learning classification models that achieved high predictive accuracy on the validation set.
  • Visualized model performance and feature distributions to communicate results to academic reviewers and peers.
Heart Disease Identification Using ML
Tools Used: SQL, Python, Pandas, scikit-learn, Power BI
  • Queried and aggregated healthcare datasets using SQL to prepare a clean dataset for modeling and analysis.
  • Performed data cleaning and outlier handling in Python to ensure reliable model training and evaluation.
  • Built classification models using scikit-learn and validated performance achieving solid classification accuracy.
  • Presented model findings and risk indicators through Power BI dashboards to illustrate insights to stakeholders.

Education

Rivier University
Master of Science in Computer Science • Nashua, NH • Jan 2023 – Dec 2024
Coursework: Operating Systems, Computer Architecture, Networking Technologies, Computer Security, Data Mining, Algorithms, Database Management Systems, Object-Oriented Design, Java Programming, Information Technology, Software Engineering Fundamentals
Vignan Institute of Technology and Sciences
Bachelor of Engineering in Computer Science and Engineering • India • Jul 2018 – Jun 2022

Powered by Drivetube · Create your own profile at drivetube.ai