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Click here or scroll down to respond to this candidateCandidate's Name
DATA ANALYSTEmail: EMAIL AVAILABLE Phone: PHONE NUMBER AVAILABLESUMMARYData Analyst with over 3+ years of experience in optimizing financial data workflows, enhancing data integrity, and creating insightful visualizations for strategic decision-making.Proficient in Python, R, and SQL, with extensive experience using libraries such as NumPy, Pandas, Matplotlib, Scikit Learn, and Seaborn to streamline data preprocessing and analysis.Skilled in managing databases using MySQL, Oracle, MongoDB, and PostgreSQL, ensuring efficient data storage, transformation, and querying.Experienced in leveraging visualization tools like Power BI, Tableau, and MS Excel to translate complex datasets into intuitive visual representations for better stakeholder understanding.Proficient in cloud platforms, particularly Azure, including Data Lake, Blob Storage, Data Factory, Synapse, and Databricks, to enhance data integration and scalability.Demonstrates strong analytical skills in data mining, cleansing, visualization, wrangling, and warehousing, with experience applying both Agile and Waterfall methodologies for structured project management.Adept at using version control tools like Git and GitHub for seamless collaboration and code management, and in developing data quality scripts, dynamic dashboards, and advanced analytics for improved forecast accuracy and addressing diverse business challenges.Applied Python and Scikit Learn to develop machine learning models, enhancing financial forecasting, optimizing sales strategies, and contributing to Autism Spectrum Disorder detection research using AI. EDUCATIONUniversity of New Haven CT, USAMasters in business Analytics Database Management & Database Design, Data Mining Jan 2023 - May 2024 Bangalore Institute of Technology Bangalore, India Bachelor of Engineering in Computer Science Aug 2017 - Aug 2021 TECHNICAL SKILLSLangages : Python, R, SQLLibraries: NumPy, Pandas, Matplotlib, Scikit Learn, Seaborn, Keras, Tenserflow Databases: MySQL, Oracle, MongoDB, PostgreSQLVisualization Tools: Power BI, Tableau, MS Excel,Cloud: Azure Data Lake, Azure Blob Storage, Azure Data Factory, Azure Synapse, Azure Databricks, AWS (EC2, S3, Lambda, RDS, Redshift)Techniques: Predictive Modeling, Financial Analysis, Deep Learning, Neural Networks, CNN, RNN, NLP, A/B Testing Methodologies: Agile, Waterfall, ScrumVersion Control Tools: Git, GitHub.Analytical Skills: Data Mining, Data Cleansing, Data Visualization, Data Wrangling, Data Warehousing, Data Preprocessing, Data Profiling, Data Interpretation Tools: ETL, SSRS, SSIS, Qlikview, Microstrategy, Alteryx, SAP PROFESSIONAL EXPERIENCEBright Mind Enrichment and Schooling, CAData Analyst Jul 2024 - CurrentExtracted, transformed, and analyzed complex datasets using Python and SQL, uncovering key insights that drove operational efficiency and supported strategic decision-making processes across various initiatives.Designed and optimized PostgreSQL database structures, implementing indexing strategies and query optimizations to enhance data retrieval times and improve overall system performance.Developed interactive and visually compelling dashboards using Tableau and Excel, translating intricate data patterns into accessible visualizations that facilitated better stakeholder understanding and engagement.Leveraged Azure cloud technologies, including Azure Data Factory and Databricks, to architect and deploy scalable ETL pipelines, enabling real-time analytics and reporting capabilities.Conducted data mining and cleansing operations, applying statistical analysis techniques to identify trends, correlations, and improve data quality and accuracy across multiple projects. KPMG, IndiaData Analyst Jun 2020 Dec 2022Optimized data preprocessing workflows using Pandas and created diverse visualizations with Seaborn, Python libraries, and Power BI, translating complex financial datasets into intuitive dashboards that enhanced stakeholder decision-making and improved financial data interpretation.Utilized MS SQL Server and MySQL platforms for effective data storage, transformation, and querying, enhancing data analysis capabilities and streamlining reporting processes for various financial stakeholders.Employed Scikit Learn to develop and deploy machine learning models, enhancing predictive analytics and enabling more accurate financial forecasting, which significantly improved business planning and resource allocation within the finance department.Engineered and implemented over 20 data quality scripts using SQL to validate successful data loads and ensure data integrity, establishing robust quality assurance measures throughout the financial data lifecycle.Enhanced forecast accuracy through advanced analytics techniques in R, developing statistical models that significantly improved business planning and resource allocation within the finance department.Integrated Azure Blob Storage and Data Factory to streamline data ingestion and transformation processes, enhancing the efficiency and scalability of financial data workflows and ensuring seamless data integration across multiple sources for comprehensive analysis and reporting.Demonstrated expertise in Text Analytics by creating 8 innovative Statistical Machine Learning solutions, addressing a wide range of financial business challenges and showcasing the project's impact on different sectors.Applied the Waterfall project management methodology to ensure structured and sequential phases in financial data projects, enabling clear documentation, precise requirements gathering, and systematic progress tracking.Engaged in the strategic design and implementation of A/B tests, carefully defining metrics to validate new user interface features, leading to improved user experience for financial data reporting tools.Implemented and managed version control using Git for all project code, ensuring efficient collaboration, versioning, and code management among the data science team, with over 100 commits tracked. Trinity Technolabs, IndiaData Analyst Intern Dec 2019 May 2020Conducted exploratory data analysis using Python libraries such as NumPy and Pandas to extract meaningful insights from structured and unstructured datasets.Executed complex SQL queries to retrieve, manipulate, and analyze data from SQL Server databases, ensuring data integrity and accuracy, and optimized SQL queries for performance, reducing data retrieval times and enhancing efficiency.Created interactive and dynamic visualizations in Tableau, including charts, graphs, and heatmaps, to present analytical results effectively, and enhanced dashboards with advanced features like drill-downs, filters, and custom visuals, facilitating deeper data exploration and informed decision-making.Applied data cleaning and wrangling techniques to preprocess raw data, including handling missing values, outliers, and inconsistencies, using Python and SQL.Collaborated with cross-functional teams in an Agile environment, participating in sprints, stand-up meetings, and retrospective sessions to ensure project alignment and timely delivery.Used Git for version control to manage and track changes in the codebase, facilitating seamless collaboration and maintaining code integrity across development cycles.PROJECTSCOVID-19 Chest X-ray Image Classification (Python, PyTorch, CNN) Developed a deep learning model using Python, PyTorch, and Convolutional Neural Networks (CNNs) like AlexNet and ResNet18 to classify chest X-ray images into normal, COVID-19, and viral pneumonia categories. Implemented data preprocessing and image augmentation techniques to improve model robustness and generalization. Evaluated the model's performance using metrics such as accuracy, precision, and recall, achieving over 95% accuracy in COVID-19 detection. This project demonstrates the potential to provide healthcare professionals with a reliable and efficient preliminary diagnostic tool for identifying COVID-19 and other viral infections. Sales Forecasting Using ARIMA (Python, Time-Series Analysis, Statsmodels) Developed a sales forecasting model using the ARIMA (Auto Regressive Integrated Moving Average) approach to predict future sales trends based on historical data. Leveraged Python and its statistical libraries, such as pandas and statsmodels, to preprocess and analyze time-series data. Implemented the ARIMA model to identify patterns, seasonality, and trends in sales, enabling accurate forecasting. Evaluated model performance using metrics like Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) to ensure reliability. The project provides valuable insights for making data-driven decisions to optimize inventory management and improve sales strategies. School Dropout Analysis (PowerBI,Data Analysis, EDA, Machine Learning) Conducted an in-depth analysis to identify key factors contributing to student dropouts, focusing on socioeconomic status, attendance patterns, and parental involvement. Utilized data analysis techniques and machine learning models to uncover actionable insights aimed at improving student retention rates. Developed strategies for early intervention and increased parental engagement to help schools reduce dropout rates and support at-risk students. PUBLICATIONSPrediction of Autism Spectrum Disorder based on Machine Learning Approach International Research Journal of Engineering and TechnologyUtilized Python-based Machine Learning algorithms to detect early signs of autism spectrum disorder (ASD), analyzing data for accuracy and time efficiency. This approach enhanced communication about ASD diagnosis by leveraging Python's capabilities in data processing, modeling, and algorithm implementation. |
