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Click here or scroll down to respond to this candidate Candidate's Name
PHONE NUMBER AVAILABLEEMAIL AVAILABLELINKEDIN LINK AVAILABLESr. Data Analyst
PROFESSIONAL SUMMARY: Senior Data Analyst with over 9+ years of experience, expert in PostgreSQL for database management and data analysis in different domains. Experienced with Apache Hadoop for managing large datasets and distributed processing. Skilled in using Apache Spark and AWS S3 for real-time big data processing and analytics. Familiar with Cloud Technologies including Microsoft Azure, AWS Lambda, AWS Redshift, and AWS Antenna facilitating scalable and efficient cloud-based data solutions. Experienced in Azure Stream Analytics for real-time data processing and analytics in cloud environments, and skilled in managing data within Azure SQL and Microsoft Azure, ensuring scalable and security. Proficient in managing Azure Data Storage services, including Azure Blob Storage, Azure Data Lake Store, Azure Databricks and utilizing Azure Data Factory and Azure Copy for efficient data processing and management. Proficient in AWS services like Lambda and S3 for scalable cloud storage and serverless computing functions, and experienced with AWS Redshift for data warehousing solutions, optimizing data storage. Adept in data warehousing technologies, including SQL and data modeling, to ensure robust and efficient data storage solutions. Proficient in SQL for streamlined data management, adept at extracting actionable insights and optimizing queries to meet scalable business needs.
Experienced in developing Packages, Stored Procedures, Functions, Views, Materialized Views, and Database Triggers using SQL and PL/SQL. Experienced in advanced Machine learning methodologies like decision trees, random forests, support vector machines, and gradient boosting for precise predictive modeling and data-driven insights. Experienced in Machine Learning frameworks such as TensorFlow, PyTorch, Amazon SageMaker, and Azure ML, enabling the development and deployment of predictive models. Proficient in Power BI, SAP Business Objects, SSRS, QlikView, Tableau, Looker, and Data Studio, adept at creating dynamic dashboards and delivering actionable business analytics.
Expert in using Informatica, Talend, SSIS, and Alteryx for ETL processes, enhancing data integration and workflow automation.
Proficient in Multidimensional Expressions (MDX) and Data Analysis Expressions (DAX) for advanced data querying. Skilled in data mining algorithms, applying statistical analysis to discover patterns and insights in large datasets. Proficient in utilizing MATLAB for advanced mathematical modeling and simulation, alongside expertise in Matplotlib and R for statistical visualization, thereby enhancing the presentation and comprehension of data insights. Proficient in Microsoft Excel, adept at data manipulation, analysis, and visualization, utilizing macros and VBA to automate tasks, enhance business reporting, and derive actionable insights. Proficient in documenting data processes and creating insightful business reports using Confluence and Microsoft Excel.
Experienced in Source-to-Target mappings, ensuring seamless data flow and accuracy across diverse systems and platforms, facilitating effective data integration and transformation processes. Expert in Software development lifecycle (SDLC) using Scrum, Agile, and Waterfall methodologies, from system planning and technology acquisition to installation, training, and operation.
Proficient in Git, Support Vector Machine (SVN), and Mercurial for version control, ensuring collaborative and error-free development environments in data projects. Proficient in creating project artifacts like specification documents, data mapping, and analysis reports, while also serving as a collaborative team player with strong technical skills, capable of working effectively with various stakeholders to maintain a positive project environment.TECHNICAL SKILLS:Database Management
PostgreSQL, SQL, Azure SQLData Analysis & Reporting
Microsoft Excel, Power BI, SSRS, SAP Business Objects, QlikView, Tableau, Looker, Data StudioBig Data TechnologiesApache Hadoop, Apache Spark, AWS S3Programming/Scripting
R, Python (NumPy, pandas), MATLAB, R, MATLABMachine Learning
TensorFlow, PyTorch, Amazon SageMaker, Azure ML
Cloud TechnologiesMicrosoft Azure, AWS Lambda, AWS Redshift, AWS Antenna, Azure Data Storage services, Azure Blob Storage, Azure Data Lake Store, Azure Data Factory, Azure CopyVersion ControlGit, SVN, MercurialTesting ToolsSAS Enterprise Guide, R Studio, Advance Query Tool (AQT), Teradata SQL Assistant, PyCharmETL/ Data IntegrationInformatica, Alteryx, Talend, SSISDocumentation & ReportingComprehensive documentation, reporting, dashboardingImage and Video AnalysisAWS RekognitionCollaboration ToolsSharePoint, Confluence, Microsoft Teams, Zoom, JiraAgile and Scrum MethodologiesScrum, Agile, WaterfallPROFESSIONAL EXPERIENCE:Client: Mercy Health, Cincinnati, OH Jun 2023 to till dateRole: Sr. Data AnalystRoles & Responsibilities:
Utilized SQL for complex data querying and manipulation, improving healthcare data analysis. Conducted in-depth data analysis using SQL, discovering correlations between specific treatments and patient outcomes to improve patient care. Implemented real-time data analytics solutions for electronic health records (EHRs) and medical devices, allowing for immediate response to emerging healthcare trends. Developed interactive healthcare dashboards in Tableau, providing real-time visualization and insight into patient care metrics. Generated monthly, quarterly, and annual reports on medical injectable rebates, authorizations, legal lawsuits, and pharmacy spending using Teradata SQL Designed comprehensive and integrated solutions compliant with HIPAA and Medicare regulations, with a focus on Facets architecture. Converted recurring report and analysis programs from SAS to R, Python, and SQL using tools such as Teradata SQL Assistant. Developed analytical reports using R Studio to monitor and control drug overdose and abuse, particularly focusing on opioids and narcotics in the market. Implemented machine learning models using Amazon SageMaker, predicting patient outcomes more accurately. Managed AWS S3 for robust data storage solutions for electronic health records, optimizing healthcare data accessibility and security. Integrated AWS Rekognition to verify patient identities during hospital admissions, appointments, and medication administration. Actively participated in Clinical Care Transportation (CCT) project quarterly reports and follow-ups to assess the impact of initiatives, ensuring providers implement corrective actions to enhance patient health and maintain lower copays. Employed Excel for advanced data manipulation and analysis, facilitating detailed healthcare reporting. Supported data migration of the FDA drugs list from Medispan to our database system. Attended client meetings to define requirements and data file formats for integration.
Experienced in preparing final deliverables for providers, including patient chart information for HEDIS, MED MEASURE, QPM, and similar metrics. Designed and automated data processes using Alteryx, increasing efficiency in laboratory information systems. Participated in the Medicare STARs program, analyzing strategies to improve Star ratings. Improved healthcare reporting accuracy through thorough data documentation, fostering data-driven decision-making. Streamlined operational workflows in healthcare by automating data processes, minimizing manual tasks, and enhancing precision. Utilized GIT for version control to efficiently manage changes and updates to project documentation and code. Supported healthcare data governance practices, ensuring data integrity and security. Engaged with healthcare professionals to tailor data analytics tools to meet specific needs.Environment: Teradata, R Studio, AQT, SAS, SQL, Microsoft Excel, SharePoint, Tableau, Amazon SageMaker, AWS S3, AWS Cloud services, Apache Spark ALS, AWS Redshift, Alteryx, AWS Rekognition, R, GIT.Client: Databricks, San Francisco, CA Mar 2021 to May 2023Role: Data mining specialistRoles & Responsibilities: Applied SQL expertise to manage and optimize databases, ensuring efficient data handling and storage. Crafted SQL queries for integration into SSIS packages, facilitating the transfer of data from the Raw layer to the Pre-stage layer for key entities like Accounts, Sites, and Users. Integrated Tableau for business intelligence reporting, delivering insightful dashboards and reports to executive teams. Developed predictive models like Logistic Regression using Python libraries such as NumPy and pandas to enhance business trend forecasting. Utilized TensorFlow and PyTorch for building and training advanced machine learning models like Convolutional Neural Networks and Recurrent Neural Networks, improving decision-making processes. Created dynamic reports and visualizations in Tableau to effectively communicate data analytics results to Customers and Investors. Employed Azure ML to develop and deploy machine learning models, boosting the Personalization and Recommendation Systems. Developed data pipelines utilizing Azure Data Factory, Azure Copy, Polybase, and multi-region data replication. Designed and implemented an Azure Data Factory (V2) framework with error logging, to load data into Azure SQL Data Warehouse from Azure Blob Storage and Azure Data Lake Store using the Kimball method. Performed data extraction, transformation, and loading from source systems to Azure Data Storage services, employing Azure Data Factory, SparkSQL, T-SQL, and U-SQL in Azure Data Lake Analytics. Configured Jupyter Notebook environments for data science teams, enhancing collaborative data analysis and model development. Implemented machine learning algorithms using MATLAB, addressing complex data challenges in the software services sector like Performance Monitoring and Optimization. Developed data mining applications using Azure ML, extracting valuable insights from large datasets to inform business strategy. Utilized Python for scripting and automation, streamlining analytics processes and reducing manual intervention. Employed Excel for data manipulation and reporting, providing support for quick decision-making in business operations. Facilitated team collaboration using Confluence, sharing insights, and maintaining alignment across project teams. Worked within Agile and Scrum methodologies, ensuring timely delivery of analytics projects in a dynamic environment. Led scrum meetings to improve team communication and project tracking, while documenting use cases and analytics findings to support ongoing software development with clear guidance.Environment: SQL, Python (NumPy, pandas, TensorFlow, PyTorch), Tableau, Azure ML, Azure SQL, Azure Blob Storage, Azure Data Lake Store, Azure Data Factory, Azure Data Storage services, Azure Copy, MATLAB, Jupyter Notebook, Excel, Confluence, SSIS.Client: JPMC, New York, NY. Nov 2018 to Feb 2021Role: Data Analyst/Data Visualization Analyst Roles & Responsibilities: Enhanced data insight delivery by developing interactive dashboards and visualizations using Power BI and Qlik Sense. Utilized Microsoft Azure for cloud-based data storage and analytics, providing scalable solutions in financial data management. Utilized Matplotlib for creating detailed financial charts and graphs, aiding in the visualization of customer data, risk data, and compliance data. Utilized SQL for Financial Performance Analysis, supporting in-depth data analysis and reporting needs in the financial sector. Managed the monitoring of financial transactions made with Visa, MasterCard, and Amex cards via Fraud Case Management System (FCMS) to identify discrepancies and detect potential fraud. Utilized R, and Azure Stream Analytics for comprehensive risk assessment, and market data processing efficiency. Implemented Data Masking and Anonymization in Azure Stream Analytics, safeguarding sensitive financial data during real-time processing. Developed Option Pricing Models and algorithms in MATLAB, optimizing risk management and investment strategies. Developed and maintained data warehouses for transaction data, customer information, and audit trails using Azure SQL, ensuring robust data management and scalability in financial operations. Managed data visualization projects to visualize financial performance metrics using Data Studio, providing customized financial insights and analytics to stakeholders. Conducted time series analysis and regression analysis using R, delivering predictive insights and trend analyses to guide financial strategies. Implemented Data Masking and Anonymization in Azure Stream Analytics, safeguarding sensitive financial data during real-time processing. Reviewed and recommended improvements for key accounts, ensuring accurate payment of warranty claims and cost savings. Produced monthly ad hoc reports using Microsoft Excel tools to support month-end closing tasks and deadlines. Led the creation, integration, and deployment of the Pricing Control Access database through SharePoint, implementing query reports to minimize pricing discrepancies across Manufacturing, Sales, and accounting departments. Performed weekly accounts receivable (A/R) audits in Azure SQL to maintain up-to-date merchant accounts and resolve any outstanding items. Conducted thorough audits to verify and align price books with billing invoices for assigned merchants. Orchestrated stakeholder meetings with investors to review data insights and dashboards created with Qlik Sense, ensuring alignment with business goals.Environment: Power BI, Qlik Sense, SQL, Looker, MATLAB, R, Azure Stream Analytics, Azure SQL, SharePoint, Data Studio, Matplotlib, and Microsoft Excel.Client: InfraSoftTech, Pune, India Feb 2017 to Jun 2018Role: Database AnalystRoles& Responsibilities:
Designed and maintained SQL data models, enhancing database efficiency and accuracy for client needs, while ensuring data integrity and security within industry standards. Developed interactive Power BI dashboards and reports, facilitating informed decision-making through visual data presentations. Implemented data mining algorithms to extract meaningful patterns from large datasets, supporting business intelligence efforts and conducting statistical analysis using DAX and MDX. Maintained SSRS reports, providing reliable business intelligence for decision-making, and integrated Git for version control in data projects, enhancing collaboration and code integrity. Leveraged SQL expertise in managing databases and conducting comprehensive data analysis, ensuring efficient data handling, storage, and transformation projects for business operations.Environment: SQL, Power BI, DAX, MDX, SAP Business Objects, SSRS, and Git.Client: Metalyst Forgings Limited, Pune, India Nov 2014 to Jan 2017Role: Data analyst Roles & Responsibilities: Employed PostgreSQL and SQL for enhanced database management and manipulation, facilitating improved data access and analysis. Utilized Microsoft Excel for advanced data manipulation and visualization, supporting detailed manufacturing reports, and developed dynamic QlikView dashboards for enhanced strategic decision-making. Managed Apache Hadoop and Apache Spark implementations, processing large datasets to drive improved business intelligence and accelerate data analysis tasks. Implemented version control with Git for enhanced collaboration and code management in data projects, while employing Informatica for efficient ETL processes to automate data transformation and integration. Developed insightful business intelligence solutions and interactive visualizations using Power BI, supported by comprehensive documentation of data processes to ensure reporting accuracy and consistency, and leveraged analytical skills in utilizing Hadoop and Spark for addressing complex data analysis challenges effectively.Environment: PostgreSQL, SQL, Microsoft Excel, QlikView, Apache Hadoop, Apache Spark, Git, Informatica, Power BI.Education: Bachelor of Technology (B. Tech) in Information Technology from Osmania, Hyderabad, Telangana, India. - 2014 |
