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Click here or scroll down to respond to this candidateCandidate's Name
PHONE NUMBER AVAILABLE EMAIL AVAILABLELinkedIn Portfolio GitHubObjectiveA Rationale Data Analyst with 4.5 years of specialized experience in SQL Database Platforms, R, and Python. TECHNICAL SKILLSPlatforms: Tableau, Power BI, Google Data Studio, R Studio, Jupyter Notebook, Apache Hadoop, Spark, Azure ML, AWS S3, AWS Lambda, Excel, Power Query, SPSS, SAS, DAX, Google Analytics. Programming Languages: Python, R, SQL, JavaScript, HTML5, CSS3, C++. Machine Learning & Data Science: Scikit-learn, TensorFlow, Keras, PCA, Regression Models, Classification Models, Clustering, Time Series Analysis, Neural Networks. Excel, Power Query, SPSS, SAS, DAX, Google Analytics. Certification: Google Data Analytics Professional Certificate (Link) April 2024 - August 2024. Micro-Certification: Data Cleaning, Data Mining, Advanced Excel, Predictive Analytics, Data-Driven Decision Making, Data Visualization, Data Wrangling, A/B Testing, Hypothesis Testing. PROFESSIONAL EXPERIENCETechnical Data Analyst University of Memphis at Memphis. Aug 2022 - May 2024 Collaborated with cross-functional teams to identify data-driven insights and ensure timely resolution of data- related technical issues, improving overall data integrity. Maintained and managed large datasets, including cleansing and transforming data from various sources, enhancing data availability for analysis. Developed Python scripts and SQL queries for data extraction, transformation, and loading (ETL) to streamline data flow and ensure data accuracy in reporting and analysis. Created automated data validation frameworks to ensure the integrity of data pipelines and analysis, identifying potential data anomalies and addressing them promptly. Designed and implemented integrations with external platforms for data extraction, leveraging APIs for real-time data collection and enhancing predictive modeling. Presented analytical insights and data visualizations to stakeholders, contributing to data-driven decision-making and the success of key business projects. Experienced in Agile/Scrum frameworks, managing data analytics projects, prioritizing tasks, and measuring progress through velocity and capacity planning. Junior Data Analyst, Dhanwin Software Developers June 2020 June 2022 Created detailed reports and automated workflows for data imports related to incident management, service requests, and system performance, improving data accessibility and visibility for business decisions. Collaborated closely with business stakeholders to gather and analyze detailed requirements, translating them into functional data solutions aligned with organizational goals. Ensured data integrity and accuracy using data transformation scripts and import tools, improving the quality of datasets for analysis and reporting. Conducted end-to-end data analysis for various business needs, including requirement gathering, data collection, and creating visual representations for stakeholders. Customized and optimized dashboards, reports, and data visualizations to provide clear insights, enabling stakeholders to make data-driven decisions. ProjectsProject on Winery Business (Vineyard and Sales) Database Management System: Designed and implemented ER diagrams for vineyard sales databases, ensuring accurate representation of data entities, relationships, and attributes. This modeling facilitated efficient data storage and retrieval processes. Followed a comprehensive SDLC approach, including requirement analysis, design, programming, and testing, ensuring the project met all performance and security requirements. Utilized front-end technologies like HTML, CSS, and JavaScript, and back-end technologies like PHP and MySQL, to develop a functional, web application Project on Python for Inform Retrieval/Web Search: Developed a GUI-based Search Engine and Created an information retrieval system using Python's Tkinter for user-friendly query input. Applied advanced text processing techniques to retrieve and rank relevant documents. Implemented TF-IDF and Cosine Similarity and Utilized Scikit-learns TF-IDF Vectorizer and cosine similarity to compare and rank documents based on user queries, improving search accuracy. Employed NLTK for tokenization and data cleaning, enhancing the quality of document parsing and ensuring accurate retrieval results from a diverse set of text files. EDUCATION Master of Science in Data Science, University of Memphis at Memphis, TN 08/2022 - 04/2024 Master of Arts, Public Administration, Indira Gandhi National Open University INDIA. 07/2016 06/2020 |
