Data Analyst Machine Learning

Saichandana Gavva

913-***-**** **************@*****.***

Summary

Analytical and detail-oriented aspiring Data Analyst with hands-on experience in data visualization, predictive modeling, and statistical analysis through internships and projects. Proficient in Python, SQL, and Tableau, with a strong background in data cleaning, data mining, and machine learning models, eager to drive insights for organizational growth. Technologies

• Languages & Tools: Python, SQL, R, MATLAB, Git, Jupyter

• Libraries: Pandas, NumPy, Scikit-learn, Matplotlib

• AI/ML: Prompt engineering, model evaluation, logic testing

• Visualization: Tableau, Power BI, Excel

• Other: Mathematical modeling, performance metrics, dashboarding Internships

RadicalX – Data Science Intern Dec 2024 – Present

• Conducted market research and competitive analysis using data mining techniques to refine marketing strategies, identifying trends across 10+ pharmaceutical product lines.

• Performed data cleaning and analysis on sales datasets using Python and Excel, creating Tableau dashboards that improved decision-making efficiency by 20%.

• Delivered insights on pricing adjustments, resulting in a 5% profit margin increase through predictive modeling. Quadrant Resources – Data Analyst Jul 2021 – Jun 2023

• Analyzed structured and unstructured datasets using Python and SQL, delivering insights that improved decision-making efficiency by 25% across 10+ projects.

• Created dashboards and reports with Tableau to visualize trends and anomalies in customer and product data, reducing analysis time by 30%.

• Designed and executed logic-based testing protocols for data pipelines, ensuring 98% data accuracy in production environ- ments.

Projects

Fintech Fraud Detection and Behavior Analysis

• Analyzed big data in fintech using Python and SQL for customer behavior prediction and fraud detection, reducing false positives by 12%.

• Conducted data mining to explore digital transformation, integrating datasets from 3 financial services for actionable insights.

• Provided recommendations to improve fintech security using statistical analysis, decreasing fraud incidents by 10%. Bank Telemarketing Success Prediction Using Machine Learning

• Built machine learning models (XGBoost, Random Forest) using Scikit-learn to predict bank telemarketing success, achieving an F1 score of 0.85.

• Performed data cleaning and preprocessing on a dataset of 10,000+ entries, including feature encoding and scaling with Pandas and NumPy.

• Visualized campaign trends using Matplotlib, aiding stakeholders in targeting strategies. Education

M.S. in Computer Science University of Central Missouri, Warrensburg, MO Aug 2023 – May 2025 B.Tech in Electronics and Communication Engineering IIIT Basar, Telangana, India Skills

Data Visualization, Predictive Modeling, Statistical Analysis, Data Cleaning, Data Mining, Machine Learning Models, Tableau, Python, SQL, Scikit-learn, Pandas, NumPy, Excel

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