Data Analyst with less than a year in SQL, Python & Data Visualization
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented Computer Science Graduate, skilled in translating business requirements into analytical dashboards and actionable insights. Experienced in SQL, Python, data exploration, and BI dashboard development to support data-driven decision-making. Strong understanding of AI/ML concepts, statistical outputs, and cross-functional collaboration with Data Engineering and Data Science teams to deliver customer-focused analytics solutions.
Malla Reddy College of Engineering and Technology
Bachelor of Technology · Computer Science & Engineering-AIML
June 1, 2021 – June 1, 2025
M.P.R.M Sri Viswasanthi Mahila Junior College
Intermediate Education · PCM
June 1, 2019 – April 1, 2021
Holy Faith English Medium High School
Secondary Education
March 1, 2018 – March 1, 2019
Cardiovascular Disease Prediction
June 1, 2025 – June 1, 2026
Orchestrated the development of a Logistic Regression model to predict cardiovascular disease (a leading cause of heart attacks), achieving 86.81% test accuracy and 86.74% training accuracy. Performed data preprocessing (missing value imputation, feature scaling, categorical encoding) to ensure high-quality model inputs. Conducted exploratory data analysis (EDA) to uncover key correlations between patient health indicators (cholesterol, blood pressure, BMI, age, lifestyle) and disease risk. Optimized model performance through feature selection and hyperparameter tuning, improving accuracy and interpretability. Evaluated predictive power using confusion matrix, ROC-AUC, precision, recall, and F1-score for reliable performance assessment. Built a real-time prediction pipeline, enabling classification of new patient records and supporting early diagnosis. Enhanced healthcare outcome predictions by ~26%, contributing to proactive patient care and improved well-being
Customer Analytics Dashboard
June 1, 2025 – June 1, 2026
Extracted and transformed datasets containing 50,000+ records using SQL queries. Performed data profiling and validation ensuring accuracy against control totals. Built interactive dashboards visualizing KPIs, customer trends, and performance metrics. Converted analytical findings into business-ready insights for decision-making. Applied statistical understanding to interpret predictive model outputs.
Sales Data Analysis & Insight Generation
June 1, 2025 – June 1, 2026
Analyzed large retail-style datasets to identify purchasing patterns and revenue drivers. Conducted exploratory data analysis improving insight discovery efficiency by 30%. Generated analytical reports translating raw data into actionable recommendations. Collaborated with simulated DE/DS workflow for model result interpretation.
AWS Academy Graduate-AWS Academy Cloud Foundation
AWS Academy
June 1, 2026 – Present
The Complete Python Developer- Udemy
Udemy
June 1, 2026 – Present
Salesforce Developer Virtual Intern
Salesforce
June 1, 2026 – Present
Prompt Design in Vertex AI Skill Badge-Google Cloud
Google Cloud
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying data analysis and machine learning techniques. The diversity of projects (cardiovascular disease prediction, customer analytics, sales data analysis) shows a broad interest in different data domains. The certifications in AWS, Python, Salesforce, and Google Cloud indicate a commitment to continuous learning and skill development, which aligns with a growth-oriented culture. However, all projects are academic, and there is no professional experience, which limits the assessment of cultural fit in a corporate environment.
Soft Skills & Operational Fit
The candidate's project descriptions highlight collaboration, client communication, and presentation skills, indicating a foundational understanding of cross-functional teamwork. The focus on translating technical findings into business insights suggests an operational fit for roles requiring data-driven decision support. However, without direct work experience, the practical application of these soft skills in a professional setting is yet to be validated.