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Click here or scroll down to respond to this candidateCandidate's Name
Kansas City, Missouri EMAIL AVAILABLE PHONE NUMBER AVAILABLE LINKEDIN LINK AVAILABLETECHNICAL SKILLSProgramming Languages: Java, C, C++, Python, JavaScript, HTML, CSS, R, PS Query Databases: MySQL, MongoDB, PostgreSQL, OracleDB, NoSQL, SQL Cloud Platforms: AWS, Azure, Oracle, Google Cloud Platform Tools and Technologies: Power BI, Tableau, RStudio, Visual Studio, Git, GitHub, Juypter Notebook, Google Colab, Anakonda, Spread Sheets, Excel, Advanced ExcelOperating Systems: Windows, Mac OS, LinuxEDUCATIONUniversity of Missouri, Kansas City, Missouri (GPA:3.66/4) Graduated: May 2024 Master of Science: Computer ScienceInstitute of Aeronautical Engineering, Hyderabad, Telangana (GPA:8.24/10) Graduated: May 2022 Bachelor of Science: Electronics and Communication Engineering PROFESSIONAL WORK EXPERIENCEStudent Technical Assistant, Part-time Jun 2023 May 2024 University of Missouri-Kansas City, Kansas City, Missouri Improved SQL queries by implementing indexing and partitioning techniques, significantly reducing data retrieval times by 30% and enhancing overall database efficiency and performance. Automated data cleaning tasks using Python with Pandas, cutting down manual processing time by 50%. Established a MySQL database to centralize over 1,000 student records, improving data access speed by 40%. Created Tableau dashboards and SSRS reports to support data analysis and reporting needs. Led a data migration project using SSIS for ETL, finishing two weeks ahead of schedule with no data loss. Trained over 50 users on SQL, Excel, and Tableau, leading to a 25% increase in effective use of these tools. TECHNICAL PROJECTSCustomer Segmentation Apr 2024 Developed a customer segmentation model using k-means clustering on transaction data, identifying 5 groups. Used Python and SQL to preprocess data and perform clustering, cutting processing time by 30%. Conducted in-depth analysis of purchasing patterns within customer segments, using SAS for statistical analysis. Visualized clustering results using Matplotlib and Seaborn for clear and informative presentations. Delivered insights into customer segments, resulting in a 10% improvement in decision accuracy. Predictive Maintenance System for Equipment Failure Oct 2023 Constructed a predictive maintenance model using Random Forest and Support Vector Machines. Employed time-series analysis and Principal Component Analysis (PCA) for feature engineering. Measured model performance using Precision, Recall, and F1-Score, leading to a 20% improvement in accuracy. Created interactive Tableau dashboards, integrating confusion matrices and ROC curves to present insights. Big Data Analytics of Mobile Applications Jan 2023 Utilized Hadoop tools (HDFS, MapReduce, Hive) to efficiently process and analyze large-scale mobile data. Analyzed user metrics and location-based patterns, effectively visualizing the data with Tableau and D3.js. Set up real-time data pipelines, reducing data ingestion time by 50% and streamlining processing and storage. Built HiveQL scripts to query and aggregate data, enabling faster extraction of insights from mobile data. Integrated Hadoop with Spark and Pig, optimizing workflows and increasing processing efficiency by 35%. CERTIFICATIONSGoogle Data Analytics Professional CertificationRELEVANT COURSEWORKData Structures and Algorithms, Object-Oriented Programming, Principles of Big Data Management, Business Economics and Financial Analysis, Data Visualization, Introduction to Statistical Learning, Information Security Assurance |
