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Click here or scroll down to respond to this candidateCandidate's Name
PHONE NUMBER AVAILABLE EMAIL AVAILABLEOBJECTIVEMotivated Data Analyst with 2 years of experience in collecting, analyzing, and transforming data into actionable insights using advanced data analytics tools and techniques. Proficient in leveraging data visualization tools, partic- ularly Power BI and Tableau, to drive performance improvements through data-driven strategies and training plans. Skilled in data engineering and analysis, I apply cutting-edge techniques to convert complex datasets into strategic solutions that enhance decision-making and drive organizational success. EDUCATIONMaster of Data Science, University of Alabama at Birmingham GPA-4.0 2022 - 2024 Relevant Coursework: Statistics, Database Systems, Data Mining, Machine Learning, Deep Learning, Quantitative Analysis for Managers and Advanced Algorithms and Data Structures. Bachelor of Computer Science, GNITS 2017 - 2021SKILLS & INTERESTSLanguages Python, Java, JavaScript, C, C#RDBMS Terraform, SQL Server, PostgreSQL, MongoDB, Snowflake Frameworks Spring Boot, Hibernate, Jenkins, Django, Flask, Tensorflow, Py- torchETL Tools SQL Server Integration Services (SSIS), Apache Kafka Web Development HTML5, CSS, jQuery, React, Node.js Collaboration Tools JIRA, ConfluenceML & DL Algorithms Supervised and Unsupervised Algorithms, PCA, Boosting Al- gorithms,CNN, Faster-RCNN, Transformers, BERT, Large Lan- guage ModelsData Processing & Analysis Libraries Numpy, Pandas, Scikit-learn, NLTK, Scipy Data Visualizaton Tools Power BI, Tableau, Matplotlib, Plotly, Seaborn Cloud Platforms AWS(Lambda, S3, RDS, SageMaker), Azure (Function Apps, Blob Storage), GCPOperating Systems Windows, LinuxAgile Methodologies ScrumEXPERIENCEData Analyst 2020-2022Accenture Hyderabad, IND Leveraged advanced SQL queries and complex joins to extract and manipulate large datasets from relational databases, integrating data from various sources. Conducted in-depth exploratory data analysis using Python to uncover hidden patterns, leading to a 15% increase in quarterly revenue through more targeted sales strategies. Architected and deployed dynamic, multi-layered dashboards in Power BI and Tableau with interactive filters, drill-down capabilities, and automated refresh schedules, providing real-time visibility into KPIs. These dash- boards reduced manual reporting efforts by 40%, enhanced data transparency across departments, and facilitated swift decision-making. Implemented robust data governance and validation frameworks that automated data quality checks using Python and Excel VBA, reducing data inaccuracies by 25% and ensuring consistent, high-quality reporting across key business functions. Collaborated with cross-functional teams to translate business needs into data-driven solutions. Delivered ana- lytical insights that optimized multi-channel marketing campaigns. Worked closely with stakeholders to understand their needs and deliver customized analytical solutions. Im- proved client satisfaction scores by 10% through targeted data insights. Presented data findings to senior management, aiding strategic planning. Enhanced collaboration and communication across teams. Contributed to the adoption of Agile methodologies to improve collaboration and speed up project deliveries. Through the implementation of Scrum and Kanban, achieved a 15% increase in project delivery speed and a 20% boost in team productivity. used Power BI to visualise data in a comprehensive way, giving stakeholders access to reports and dashboards that made data-driven decisions easier. This improved communication and understanding throughout teams. Orchestrated direct communication with vendors through biweekly calls, ensuring 100% project goal alignment and reducing miscommunication-related delays by 15%. PROJECTSFake News Detection: Developed a platform to detect Fake News by using Natural Language Processing and Deep Learning. Applied data preprocessing with TF-IDF, and developed a Convolutional Neural Network (CNN) for effective pattern recognition in text. This solution processes input to ascertain news veracity, achieving a remarkable accuracy rate of 90%.Crop Prediction: Developed a Crop Prediction tool with advanced Machine Learning techniques, predicting optimal crops based on temperature, pH, rainfall, and humidity with 92% accuracy. Utilized HTML, JavaScript, CSS for the UI, aiding data-driven agricultural decisions. Smart Budget Planner: A web-based application designed to assist users in managing their finances through intelligent budgeting and spending tracking. Implemented using Angular for the frontend, Python Flask for the backend, and integrated with financial data APIs.Spotify Music Analytics: Collected and preprocessed Spotify data which includes artist information and music features such as energy and danceability, using normalization and transformation techniques,Applied Machine learning models such asnKNN and Decision Trees to gain insights from the data achieving an accuracy of 95%,Utilized PowerBI to visualize data insights for clear understanding of genre preferences, trending genres, and artist performance over time.Habit Analysis: Developed an Angular-based web application for storing customized questions and answers, with data stored in MongoDB database,Utilized PowerBI to visualize data insights, enabling daily habit analysis such as time spent on phone,study and data analysis has been conducted to identify trends and patterns. |
