Data Analyst Machine Learning
Resume:
Tarun Kumar Bandi
Irving, TX, ***** +1-903-***-**** ************@*****.***
PROFESSIONAL SUMMARY
Data Analyst with over 5 years of experience in data integration, analysis, and visualization across healthcare, retail, and financial domains. Proficient in leveraging tools like Python, SQL, Power BI, Tableau, and cloud-based solutions to design and implement data-driven solutions that optimize operational efficiency and decision-making. Skilled in ETL processes, data modeling, and advanced analytics, with a strong focus on data quality, compliance, and actionable insights. Adept at collaborating with cross-functional teams to deliver impactful business intelligence solutions and drive strategic growth.
TECHNICAL SKILLS
Category
Technologies
Programming Languages
Python, SQL, Java, R Programming, C, C++, Shell Scripting, MATLAB
Big Data Technologies
PySpark, Spark, Hadoop, MapReduce, Apache Flink, EC2
Machine Learning & AI
Machine Learning, Clustering, Regression, Statistical Modeling, Artificial Intelligence
Operating Systems
UNIX, Windows, LINUX, Mac OS X
Databases
Oracle 11g, Microsoft SQL Server, PostgreSQL
Web Technologies
JavaScript, XML, JSON, HTML
Cloud Technologies
AWS S3, Azure, GCP
Reporting Tools
Tableau, Power BI, SSIS
Version Controls
Git, GitHub
ETL Tools
Apache Kafka, AWS Glue
WORK EXPERIENCE
CVS (Dallas, TX) 2024 May - Present
Data Analyst (Healthcare Performance Dashboard Development)
•Collaborated with healthcare teams, including doctors, administrators, and nurses, to understand data needs, assess budget deviations, and identify cost-saving opportunities, leading to improved operational efficiency.
•Analyzed patient data and healthcare metrics using Python and SQL to determine key performance indicators (KPIs) related to patient care, hospital efficiency, and clinical outcomes.
•Conducted detailed variance analysis and predictive modeling to forecast patient demand and optimize hospital resource allocation, addressing staffing needs and improving patient care.
• Designed data models and created comprehensive data validation frameworks to ensure accurate data alignment with industry standards such as HIPAA.
•Defined ETL (Extract, Transform, Load) processes, utilizing Python and SQL Server Integration Services (SSIS) to streamline the integration of healthcare data from multiple EHR systems and other platforms into a centralized data warehouse.
•Utilized Power Query in Microsoft Excel to standardize large datasets for further analysis, enhancing data consistency and processing efficiency.
•Developed automated ETL pipelines using Python and SSIS, significantly improving the efficiency of healthcare data processing and integration.
•Built interactive Power BI dashboards to visualize critical healthcare metrics (e.g., patient wait times, readmission rates, treatment effectiveness), enabling real-time monitoring and data-driven decision-making.
•Crafted complex SQL queries to support ad-hoc analysis of patient outcomes, treatment costs, and resource utilization, promoting actionable insights and supporting data-driven healthcare strategies.
•Performed data profiling, validation, and integrity checks on raw healthcare data to ensure accuracy, compliance, and consistency across datasets.
•Implemented rigorous data validation and integrity checks within SQL Server Reporting Services (SSRS) to enhance report accuracy and reduce discrepancies in healthcare reports.
•Conducted stress tests and variance analysis on machine learning models, ensuring accuracy in demand forecasting, staffing, and supply chain management.
• Automated report generation workflows using Python scripts, SQL, and Microsoft Office tools, significantly reducing manual reporting efforts and expediting reporting cycles.
•Coordinated with IT teams for seamless integration of new data sources from healthcare devices, patient monitoring systems, and clinical databases into existing data warehousing systems.
•Managed version control for ETL pipelines and Power BI dashboards using GitHub, enabling efficient tracking of changes, collaboration, and enhancement of data workflows.
•Monitored and maintained data pipelines to ensure continuous data flow and accuracy for real-time healthcare analytics, supporting ongoing patient care and operational decision-making.
•Routinely optimized SQL queries and data transformation processes to meet evolving data needs and performance requirements within the healthcare environment.
•Delivered regular presentations of actionable insights, empowering senior healthcare management to make strategic decisions on patient care, budgeting, and resource allocation.
ENVIRONMENT: Python, SQL, SSIS, APIs, Power BI, Tableau, Power Query (Microsoft Excel), SQL Server, EHR systems integration, SSRS, GitHub, cloud-based solutions, data pipeline monitoring, automation, HIPAA compliance, data profiling, data validation, and data modeling.
Nike (Beaverton, OR) 2023 Aug – 2024 Apr
Data Analyst (Retail Performance Dashboard Development))
•Participate in daily stand-up meetings and sprint planning sessions to collaborate with the team, share progress, and align with project goals and objectives.
•Analyze and develop STM (Source to Target Mapping) for data integration projects. Create mappings to transform and load data from source systems to target systems.
•Developed and maintained data visualizations and reports to support retail performance analysis and decision-making. Utilized Tableau to create interactive and dynamic dashboards for stakeholders.
• Collaborated with cross-functional teams to design and implement data governance processes and ensure data quality. Ensured data accuracy and integrity by implementing data validation checks and data cleansing processes.
• Analyzed large datasets using SQL and data modeling techniques to identify trends and insights. Created data mart designs and implemented ETL processes to support data analysis and reporting.
•Worked with stakeholders to identify business requirements and developed business intelligence solutions to meet those needs. Utilized agile methodologies to iterate and refine solutions based on stakeholder feedback.
•Developed and maintained database designs and implemented data warehousing solutions to support Supply-Chain performance analysis. Ensured data security and compliance with company policies and regulations.
•Collaborated with IT teams to implement data integration solutions and ensure seamless data flow. Utilized APIs to integrate with external data sources and systems.
•Analyzed and optimized data processing workflows to improve efficiency and reduce costs. Implemented data quality checks and data monitoring processes to ensure data accuracy and integrity.
•Worked with stakeholders to develop and implement data-driven solutions to drive business growth and improvement. Utilized machine learning algorithms and predictive analytics techniques to identify trends and insights.
•Developed and maintained technical documentation for data systems and processes. Ensured knowledge transfer and training for stakeholders on data systems and processes.
•Analyze large datasets to identify trends, patterns, and insights. Create visualizations to communicate findings to stakeholders using Confluence and Jira.
•Collaborated with IT teams to implement cloud-based data solutions and ensure scalability and reliability. Utilized DevOps methodologies to iterate and refine solutions based on stakeholder feedback.
•Analyzed and optimized data storage solutions to improve efficiency and reduce costs. Implemented data backup and disaster recovery processes to ensure data security and integrity.
ENVIRONMENT: Python, SQL, SSIS, Tableau, Power BI, APIs, Confluence, Jira, GitHub, DevOps methodologies, ETL processes, data modeling, data warehousing, data validation, machine learning algorithms, predictive analytics, cloud-based solutions, data governance, data backup and disaster recovery processes.
Accenture Solutions Pvt. Ltd 2019 May – 2022 June
Data Analyst (Finance Data Integration and Reporting)
•Worked closely with financial stakeholders to define and align requirements for the ETL pipeline, ensuring it addressed the specific analytical needs of financial reporting and compliance.
•Analyzed and integrated financial data from various sources, including CSV files, Excel sheets, and SQL databases, to generate comprehensive insights into company performance, revenue, and expenses.
•Utilized Python and Pandas for data cleaning and preprocessing, ensuring the accuracy of financial data and deriving key performance metrics like profit margins, cash flow, and ROI.
•Implemented automated data processing schedules using Azure Data Factory to ensure the timely availability of up-to-date financial data for analysis and reporting.
• Consolidated and organized cleaned financial data into a centralized Azure SQL Database, facilitating efficient access for generating financial reports and analysis.
•Integrated real-time financial data from banking APIs and other third-party financial platforms, providing immediate insights into revenue trends, account balances, and financial transactions.
•Linked the Azure SQL Database with Power BI to create interactive visual reports and dashboards, providing key stakeholders with up-to-date financial metrics, enabling data-driven decision-making.
•Developed custom applications with Power Apps, allowing finance teams to easily interact with financial data and perform ad-hoc analysis without requiring deep technical knowledge.
•Employed SSIS (SQL Server Integration Services) for advanced ETL processes, improving data transformation workflows by efficiently integrating financial data from multiple sources.
•Generated detailed financial reports using SSRS (SQL Server Reporting Services), delivering comprehensive and actionable business intelligence on budget performance, forecasting, and variance analysis.
•Conducted rigorous testing to ensure data accuracy and consistency across reports, aligning financial analysis with business goals and regulatory standards.
•Documented the financial data analysis process and provided ongoing support to ensure the reliability of financial insights and reports for future audits and compliance checks.
•Streamlined financial reporting processes using Six Sigma methodologies, improving efficiency, reducing errors, and enhancing the accuracy of financial statements.
•Enhanced data security by implementing robust measures to protect sensitive financial information within the database, adhering to strict data governance and regulatory requirements (e.g., SOX compliance).
ENVIRONMENT: Python, Pandas, SQL, Azure Data Factory, Azure SQL Database, Power BI, Power Apps, SSIS, SSRS, banking APIs, ETL processes, Six Sigma methodologies, data governance, and compliance standards (e.g., SOX)
Supraja Technologies Pvt Ltd 2018 Nov– 2019 March
Data Analyst Intern (Sales Data Analysis and Forecasting)
Collected, cleansed, and processed large datasets from multiple sources, including sales records, customer information, and product data.
Used Python (Pandas, NumPy) and SQL to perform data wrangling and ensure data accuracy.
Conducted exploratory data analysis (EDA) to identify key trends, patterns, and outliers in the sales data.
Created interactive dashboards and reports using Power BI to visualize sales performance by product, region, and time period.
Applied statistical models and time series forecasting techniques (ARIMA, Holt-Winters) to predict future sales trends and seasonal patterns.
Implemented data validation checks to ensure data quality and consistency, identifying and resolving data discrepancies before analysis.
Created ad-hoc reports for different departments using Excel and Power BI, enabling cross-functional teams to make data-driven decisions in real-time.
Collaborated with the marketing and sales teams to derive insights and present findings to stakeholders.
EDUCATION
Southern Arkansas university Magnolia, Arkansas
Master of Science in Computer and Information science 2022 Aug– 2024 May
Velagapudi Ramakrishna Siddhartha Engineering College Vijayawada, India
Bachelor of Technology 2015 Jul– 2019 Apr
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