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Akhilesh Kumar - Data Analyst

jessica@daticsinc.com

Location: Detroit, Michigan, USA

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Akhilesh Gaddam +1 989-944-9488 akhileshkumar81431@gmail.com Senior Data Analyst PROFESSIONAL SUMMARY: Expert Senior Data Analyst with over 7+ years of experience in data-intensive roles. Utilized SQL Server to manage and streamline database operations, enhancing data accessibility and system efficiency. Leveraged SSRS for creating sophisticated reporting solutions that improved decision-making processes across various departments. Implemented normalized data structures to ensure data integrity and optimize query performance within enterprise applications. Designed and executed data manipulation logic using SQL, improving data processing efficiency and accuracy. Managed FTP folders for secure data transfer, ensuring compliance with data security standards and protocols. Employed SSIS for data integration and workflow solutions, significantly reducing manual data entry errors and processing time. Conducted data cleansing processes to maintain data quality, utilizing SQL and custom scripts to detect and correct errors. Performed DML operations within stored procedures to automate and secure data transactions, enhancing database performance. Developed aggregation processes to summarize data effectively, facilitating quick and accurate reporting and analysis. Created extensive documentation for data processes, ensuring clear guidelines and references for ongoing maintenance and compliance. Utilized Power BI to develop interactive dashboards and reports, providing actionable insights to business stakeholders. Enhanced business reporting capabilities by integrating SQL and Power BI, delivering customized reports to meet specific user requirements. Analyzed and identified process bottlenecks using SQL and business analytics, proposing solutions to enhance workflow efficiency. Facilitated process mapping and documentation using Microsoft Visio, improving understanding and management of business operations. Employed Lucidchart to diagram and visualize workflows, enabling clear communication of process improvements and changes. Used Bizagi to automate workflows, reducing manual intervention and streamlining business processes across functions. Implemented Arena simulation software to model business processes, predicting outcomes and optimizing operations. Conducted value stream mapping with Visio to identify waste and inefficiencies, enhancing overall process flow and productivity. Applied Kaizen methodologies to drive continuous improvement initiatives, fostering a culture of innovation and efficiency. Developed predictive models using TensorFlow and PyTorch within the insurance domain, enhancing risk assessment and pricing strategies. Utilized Python's NumPy and pandas libraries for data analysis and machine learning model development, improving predictive accuracy. Created and managed Jupyter Notebook environments for data science projects, streamlining code development and data exploration. Configured and managed Microsoft Azure environments to host and process large datasets, optimizing cloud resources for scalability. Implemented Azure ML and Databricks to build and deploy machine learning models at scale, reducing time to insights. Prepared and presented data insights using Excel and PowerPoint, effectively communicating complex data in an accessible format to non-technical stakeholders. TECHNICAL SKILLS: Programming Languages : SQL, Python, R Data Analysis Tools : Excel, Jupyter Notebook, MATLAB, Power BI Data Visualization : Plotly, ggplot2, Power BI Machine Learning Frameworks : TensorFlow, PyTorch, Azure ML Cloud Platforms : Microsoft Azure, Azure Blob, Azure Databricks, Azure Cognitive Services Business Intelligence : SSRS, Power BI Data Integration : SSIS, FTP Process Mapping Tools : Microsoft Visio, Lucidchart, Bizagi Project Management : Scrum, Agile Documentation Tools : Excel, PowerPoint, SharePoint PROFESSIONAL EXPERIENCE: Client: Epic Systems, Savannah, GA Oct 2023 to till date Role: Senior Data Analyst Roles & Responsibilities: Developed complex data analytics solutions utilizing Azure Databricks, which streamlined data processing and enhanced decision-making. Integrated AI technologies with Azure Cognitive Services to automate and optimize business processes, increasing operational efficiency. Managed extensive Azure Blob storage solutions, ensuring secure and scalable data storage across diverse project needs. Led the implementation of SharePoint integration with Databricks, facilitating collaborative data analysis and project management. Designed advanced data models using ggplot2, which provided deeper insights through sophisticated visualizations. Conducted detailed data lineage tracking with Azure, ensuring transparency and traceability of data transformations. Utilized Azure Cognitive Services to deploy custom machine learning models that predicted customer behaviors accurately. Employed Plotly in R to create interactive and dynamic data visualizations for stakeholder presentations and reports. Managed Azure SQL databases, ensuring high availability and security for critical business applications. Implemented data cataloging with Azure to enhance data discoverability and governance across the organization. Leveraged SQL extensively to perform data queries and analyses, which supported strategic business initiatives. Used Python's pandas library to manipulate and analyze large datasets, improving data quality and insights. Configured Azure Automation services to streamline repetitive tasks and processes, reducing manual workload and errors. Applied statistical analysis using R to identify trends and patterns that informed business strategy and operational adjustments. Prepared comprehensive Excel reports and PowerPoint presentations that communicated complex data findings effectively to stakeholders. Utilized Power BI to create dashboards that monitored real-time data and KPIs, enhancing business responsiveness and agility. Deployed Azure Machine Learning to build and refine predictive models, significantly improving forecast accuracy. Configured and managed Azure Data Factory pipelines for efficient data movement and transformation. Developed and maintained Azure Cosmos DB for high-performance, globally distributed applications requiring massive scale. Implemented Azure Cognitive Search to enhance data retrieval capabilities and user search experiences. Conducted data profiling and quality assessments using SQL and custom scripts to maintain high data integrity. Used Azure Logic Apps to automate workflows between cloud services and on-premises systems, enhancing process efficiency. Analyzed and visualized data using Azure Stream Analytics for real-time insights, facilitating quick decision-making. Orchestrated data integration and synchronization across multiple platforms and databases using Azure Data Factory. Documented all data processes and systems in SharePoint, ensuring that knowledge was accessible and transferable within the team. Environment: Azure Databricks, Azure Cognitive Services, Azure Blob Storage, SharePoint, ggplot2 (R), Azure, Plotly (R), Azure SQL, Python (pandas), Azure Automation, Azure Data Factory, Azure Cosmos DB, Azure Cognitive Search, Azure Stream Analytics, Azure Logic Apps, Power BI, Excel, PowerPoint. Client: Nationwide Insurance, Murfreesboro, TN Jun 2021 to Sep 2023 Role: Data Mining Specialist Roles & Responsibilities: Utilized Plotly for sophisticated data visualization projects, enabling enhanced interactive reporting capabilities in medical application development. Employed SQL for complex data manipulation and analysis, providing crucial insights to support healthcare research and development initiatives. Developed extensive data models using R, which facilitated more accurate predictions and analyses in healthcare applications. Managed projects using Microsoft Excel, streamlining data processing and reporting tasks in the medical domain. Created impactful presentations with PowerPoint to convey complex data insights to stakeholders, improving project communication and understanding. Leveraged ggplot2 for creating detailed statistical visualizations, which aided in the interpretation and presentation of complex healthcare data. Implemented Azure Cognitive Services to develop advanced machine learning models, enhancing diagnostic tools and patient care solutions. Conducted data analysis using R language to identify trends and patterns, informing critical decisions in healthcare project development. Utilized Azure Blob for secure and scalable storage solutions, ensuring data integrity and compliance in medical data handling. Integrated Azure Cognitive Services for predictive analytics, improving forecast accuracy and operational efficiency in medical applications. Employed SharePoint to manage project documentation and collaboration effectively, enhancing team productivity and data governance. Developed data cataloging solutions with Azure, ensuring organized data storage and efficient retrieval in healthcare data management. Facilitated data lineage tracking using specialized tools, providing clear audit trails and compliance with healthcare regulations. Applied advanced analytics techniques using Azure Databricks, significantly speeding up data processing and analysis in medical research. Configured Azure SQL Database for high-performance data management, supporting large-scale medical databases with high availability. Implemented data automation and integration processes using Azure Logic Apps, optimizing workflows in medical data operations. Utilized advanced analytics to extract insights from complex datasets, supporting strategic decisions in healthcare development. Developed and maintained robust data pipelines in Azure Data Factory, ensuring seamless data flow and transformation in healthcare projects. Managed secure data transfers and integrations using Azure Data Factory, maintaining high standards of data security and compliance. Leveraged AI and machine learning capabilities in Azure to develop models that predict patient outcomes, enhancing treatment plans. Conducted rigorous data quality control using SQL scripts, ensuring the accuracy and reliability of medical research data. Employed Azure Stream Analytics for real-time data monitoring, providing immediate insights into healthcare operations and patient data. Documented all processes and systems comprehensively in SharePoint, ensuring consistent knowledge transfer and regulatory compliance in healthcare data management. Environment: Plotly, SQL, R, Excel, PowerPoint, ggplot2 (R), Azure Cognitive Services, Azure Blob Storage, SharePoint, Azure Databricks, Azure SQL Database, Azure Logic Apps, Azure Data Factory, Azure Stream Analytics. Client: Comcast, Philadelphia, PA Dec 2019 to May 2021 Role: Data Analyst Roles & Responsibilities: Implemented TensorFlow and PyTorch to build sophisticated machine learning models, enhancing predictive analytics in insurance risk assessment. Used Python to develop complex data manipulation scripts, significantly improving data analysis processes within the insurance domain. Managed large-scale data storage and processing using Microsoft Azure, ensuring efficient handling of massive insurance datasets. Developed Jupyter Notebook workflows for data mining projects, which expedited the analysis and improved accuracy in predictions. Streamlined the reporting process with Power BI, enabling the creation of dynamic dashboards and reports for business stakeholders. Utilized SQL to perform advanced data queries that supported data-driven decision-making in the mutual insurance sector. Employed MATLAB for mathematical modeling, aiding in the calculation of premiums and risk assessments based on historical data. Configured and managed Python environments using Anaconda, streamlining development workflows and ensuring consistent project setups. Utilized NumPy and pandas in Python for numerical data analysis and time-series forecasting, enhancing financial forecasting models. Applied PyTorch for deep learning applications, developing models that identified patterns and anomalies in insurance claims. Integrated Azure Databricks for big data analytics, accelerating data processing and collaboration across data science teams. Leveraged Azure Machine Learning to automate model training and deployment processes, increasing efficiency in model updates. Created automated data pipelines using Azure Data Factory, which facilitated the seamless flow of data across systems. Utilized Scrum methodologies to manage project workflows, ensuring timely delivery of data projects within the insurance domain. Developed and maintained data models in Azure SQL Database, supporting robust data governance and scalability requirements. Enhanced data visualization capabilities using ggplot2 in R, providing detailed graphical representations of insurance trends. Conducted data profiling and cleansing using custom Python scripts, ensuring high data quality and reliability for analytics purposes. Leveraged Azure Logic Apps to automate workflow processes between cloud services and on-premise systems, enhancing operational efficiencies. Used TensorFlow to implement neural networks, improving the accuracy of fraud detection systems in insurance applications. Documented all project phases and outcomes in SharePoint, ensuring that project deliverables were traceable and compliance standards were met. Environment: TensorFlow, PyTorch, Python, Microsoft Azure, Jupyter Notebook, Power BI, SQL, MATLAB, Anaconda, NumPy, pandas, Azure Databricks, Azure Machine Learning, Azure Data Factory, Scrum, Azure SQL Database, ggplot2 (R), Azure Logic Apps, SharePoint. Client: Nascent Info Technologies, India Jun 2017 to Aug 2019 Role: Business Analyst Roles& Responsibilities: Utilized SQL for rigorous data analysis, ensuring accurate and actionable insights within the public safety domain. Applied data visualization tools to create comprehensive reports that improved operational decision-making and strategic planning. Managed and enhanced data quality using custom SQL scripts, ensuring reliability and accuracy of public safety databases. Developed data cleansing routines that significantly improved the integrity of data used in safety operations. Employed visualization software to graphically represent crime patterns and safety trends, aiding in public safety planning. Implemented Microsoft Excel to manage and analyze data, producing detailed reports for stakeholders and decision-makers. Conducted business analysis to identify and resolve inefficiencies in data management processes, enhancing overall workflow. Utilized R for statistical analysis, providing deeper insights into public safety data and operational effectiveness. Leveraged Power BI to develop interactive dashboards, facilitating real-time data access and analysis for quick decision-making. Managed documentation processes using Microsoft Office tools, ensuring all data procedures were accurately recorded and compliant. Developed and maintained comprehensive data documentation, providing a reliable reference for public safety operations. Utilized Azure SQL Database for secure and scalable data management, supporting extensive public safety databases. Integrated SharePoint for project management and collaboration, streamlining communication and documentation processes. Performed data profiling to identify data discrepancies and anomalies, ensuring high standards of data quality were maintained. Leveraged ggplot2 within R to enhance data presentation, making complex data sets accessible and understandable to non-technical audiences. Conducted regular data audits using SQL, maintaining stringent compliance with data governance and public safety regulations. Implemented Azure Data Factory pipelines for efficient data integration and transformation, optimizing data workflows. Documented and reported on all phases of data projects in SharePoint, ensuring transparency and accountability in public safety operations. Environment: SQL, data visualization tools, Microsoft Excel, R, Power BI, Microsoft Office, Azure SQL Database, SharePoint, Azure Data Factory, ggplot2 (R). Education: Bachelor of Technology (B. Tech) in Information Technology from JNTUH, Hyderabad, Telangana, India Keywords: artificial intelligence machine learning business intelligence database rlang trade national Georgia Pennsylvania Tennessee