Data Analytics Machine Learning

Ajith Raju Aumbati

********@***.*** +1-571-***-**** ajith008.github.io linkedin.com/in/ajithraju-aumbati github.com/Ajith008

PROFILE

Graduate Data Analytics Engineering student at George Mason University with hands-on experience turning multi-source data into clear, stakeholder-ready insights. Skilled in Google Analytics, UTM tagging, cohort/trend analysis, and building Excel/Python/SQL workflows to drive UX and content recommendations that improve outcomes.

EDUCATION

George Mason University Virginia, United States

MS in Data Analytics Engineering; GPA: 3.78 08/2024 - 05/2026 SRMIST Tamil Nadu, India

B Tech Electrical and Electronics Engineering; GPA: 3.0 07/2016 - 05/2020 TECHNICAL AND ANALYTICAL SKILLS

• Programming & Data Tools:Python (Pandas, NumPy, Scikit-learn, TensorFlow, NLTK), R, SQL (PostgreSQL, MySQL, SQL Server, Snowflake), Git, GitHub, Excel

• Data Management: ETL, data wrangling, validation, automation, and multi-source data integration

• Machine Learning & Statistics: Supervised/unsupervised learning, inferential statistics, A/B testing, NLP, predictive modeling

• Platforms: Microsoft Office Suite, SmartSheets, GCP, Confluence.

• Documentation & Reporting: PowerPoint, stakeholder reports, process documentation

• Soft Skills: Curious, reliable, team-oriented, detail-focused, strong communicator.

• Analytics Tools: Power BI, Looker Studio, Google Analytics, UTM tagging

• Platforms: Microsoft Office Suite, Azure, AWS, GCP, Confluence, SmartSheets

• Soft Skills: Intellectually curious, collaborative, detail-focused, data-driven storytelling, clear communicator with technical and non-technical stakeholders

EXPERIENCE

Application Development Associate, Accenture Solutions Pvt ltd, Hyderabad 01/2021 – 05/2022

• Built and automated data pipelines to clean, integrate, and analyze performance metrics for operational and customer datasets

• Developed dashboards using Power BI to visualize customer engagement and retention trends, aiding decision-making across departments

• Applied R,Python and SQL to analyze unstructured feedback, evaluate user sentiment, and highlight system bottlenecks .

• Supported agile teams in building scalable pipelines, ETL workflows, and RPA-style automation, reducing manual effort by 40

• Applied NLP models to unstructured text data to derive customer sentiment and improve marketing strategies

• Participated in agile sprints and code reviews, contributing to scalable data pipelines and RPA-style automation for repetitive reporting tasks.

• Supported ETL workflows, data validation, and documentation to ensure data integrity across operations and improve inventory visibility.

PROJECTS

AI-Powered Chatbot for Customer Support PROJECT LINK

• Developed an AI-driven chatbot ELISA using NLP and Generative AI to automate customer support queries.

• Implemented sentiment analysis to personalize responses and optimize user experience.

• Tools Used: Python (NLTK, TensorFlow), SQL, Google Cloud Platform (Dialogflow).

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Predictive Analytics for Diabetes Classification PROJECT LINK

• Conducted exploratory data analysis (EDA) on electronic health records (EHR) to identify diabetes risk factors..

• Built predictive models using logistic regression, decision trees, and ensemble methods.

• Integrated demographic and clinical variables to enhance prediction accuracy.

• Evaluated models using precision, recall, F1-score, and cross-validation.

• Tools Used: R, Python, Excel

Jan 2021 – May 2022

Personalized Movie Recommendation System PROJECT LINK

• Built a machine learning-based recommendation system using collaborative filtering and matrix factorization on the MovieLens dataset.

• Applied business intelligence techniques to enhance forecasting and user preference analysis.

• Tools Used: Python, KNN, Collaborative Filter, Excel SELF LEARNING PROJECTS

SQL-Sales-Marketing PROJECT LINK

• Analyzed sales performance, customer behavior, and web event conversions using SQL.

• Identified top-performing regions, accounts, and sales reps, optimizing database queries.

• Investigated customer engagement patterns and repeat purchase trends over time.

• Future enhancements include real-time data pipelines and automated performance dashboards.

• Tools Used: SQL (MySQL), Excel.

CERTIFICATIONS & PUBLICATIONS

• Microsoft Certified: Dynamics 365 Fundamentals (CRM) – Expertise in CRM data integration and automation.

• Microsoft Certified: Azure Data Fundamentals – Expertise in cloud-based data solutions, SQL, and data processing on Azure.

• Authored a research paper titled"Analyzing Obesity Patterns Among Women, Infants, and Children (WIC) Program Participants" as part of an in-class project, utilizing R, Python, SQL, and AWS for data cleaning, visualization, and analysis to gain hands-on experience with raw datasets.

• Tools Used: R,Python, SQL,AWS

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