Part-Time Power Bi

Nikshith Reddy Sheelam

• Kansas City, Missouri • ********************@*******.*** • 816-***-****

• linkedin.com/in/nikshith-reddy-sheelam

TECHNICAL SKILLS

Programming 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 Excel

Operating Systems: Windows, Mac OS, Linux

EDUCATION

University of Missouri, Kansas City, Missouri (GPA:3.66/4) Graduated: May 2024 Master of Science: Computer Science

Institute of Aeronautical Engineering, Hyderabad, Telangana (GPA:8.24/10) Graduated: May 2022 Bachelor of Science: Electronics and Communication Engineering PROFESSIONAL WORK EXPERIENCE

Student 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 PROJECTS

Customer 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%. CERTIFICATIONS

Google Data Analytics Professional Certification

RELEVANT COURSEWORK

Data 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

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