Sai Chaitanya Reddy

In Summary, as a Data Analyst in the health sector, I have played a crucial role in leveraging data-driven insights to enhance decision-making and drive positive outcomes. My responsibilities have spanned across various facets of healthcare data, and my expertise lies in translating complex datasets into actionable which helps in meeting the business requirements:

Responsibilities :

• Manage data systems for population health data integration in accordance with privacy law, and relevant data custodian and ethical approvals.
• Manage systems and processes for the delivery of integrated datasets to internal and external project investigators.
• Provide timely and efficient administration, analysis and technical support for the information technology systems, databases and application tools used within the CHeReL Data Integration Unit.
• Link health related datasets; including using Machine Learning technologies.
• Test the accuracy of the probabilistic linkage model at different cut-off points and clerical review of uncertain matches to minimize false negative matches, at the same time keeping the number of clerical reviews at a manageable level
• Participate in the development and testing of new linkage/data management, quality assurance methods and software to improve the quality and efficiency of the CHeReL's record linkage service and infrastructure.
• Develop and maintain systems for the Data Integration Unit to manage virtual repositories of current and historical population data.
• Expertise in time management skills and a good track record for delivering on deadlines.
• Liaise with external organisations on matters relating to the CHeReL database systems, encryption of files and records, and electronic exchange of data and ensure the best practices are followed for data linkage code development ( well-structured and maintainable).

Technical and Leadership with in NSW eHealth Department:

• Ability to analyze and interpret complex information from numerous sources, prepare and present analysis and reports, deal with challenges creatively and achieve business focused solutions
• Developing some meaningful insights and generate SDTM datasets using CDISC standards.
• Unpacking the skills to help researchers by providing Quote Query subsets by using SAS, SSMS, Power BI, ETL pipelines and Python for better understanding the clerical reviews.
• Generate reports by using procedures such as PROC TRANSPOSE, PROC FORMAT, PROC SUMMARY, PROC MEANS, PROC FREQ, PROC REPORT, PROC TABULATE, PROC SQL etc.
• Using Excel and SQL to collect, maintain, check correctness of data by modifying it as and when required and fetching it to generate reports using Power BI.
• Migration of existing DEV/SR/PRD environments to cloud for critical external web app that helped to achieve 20% decrease in infrastructure operating costs.
• Applied Python and R for advanced statistical analysis, predictive modelling, and machine learning, uncovering trends and informing evidence-based decision-making.

In my capacity as a Data Analyst at the Greater Metropolitan Cemeteries Trust (GMCT), I have been instrumental in harnessing data-driven insights to enhance operational efficiency, optimize services, and contribute to the organization's overarching mission of providing compassionate cemetery services to the community.

• Conducted complex data queries and analysis using T-SQL, and used Microsoft SQL Server Management Studio (SSMS) to extract, transform, and load data from multiple sources into target databases and data warehouses, resulting in improved data accuracy and efficiency.
• Created and maintained data models and data warehouses using SQL Server Analysis Services (SSAS) and SQL, and used Power BI to develop custom reports and dashboards based on these data models, resulting in improved data warehousing and analysis capabilities.
• Conducted ad-hoc data analysis and reporting using T-SQL, and used SQL Server Reporting Services (SSRS) to create custom reports and visualizations based on analyzed data, resulting in improved data-driven decision-making.
• Collaborated with team members to develop Power App for Project management and integrated with Power automate and Power BI.
• Conducted ad-hoc data analysis and reporting using SQL and Power BI, and used advanced techniques such as DAX and
• MDX to perform complex calculations and modelling, resulting in improved insights and data-driven decision-making. Performed Data Cleaning and Data Scrubbing with ETL workflows for customer report.
• Performed data extraction, storage, manipulation, processing, and analysis using Excel, Microsoft SQL-Server. Created Data Visuals for Extra tech ingoing and outgoing customer using PowerBI.
• Problems solving for bugs and errors in data with Excel, Python Panda, Microsoft SQL.

• Proficient in applying statistical techniques and developing predictive models to identify trends, patterns, and actionable insights.
• Experienced in collaborating with clients to understand their objectives, translating business requirements into data-driven solutions, and presenting findings in a clear and accessible manner.
• Skilled in creating visualizations and dashboards using tools like Tableau, Power BI, or Python libraries, translating complex data into easily understandable formats.

Tools and Technologies:

• Programming Languages: Proficient in languages such as Python and R for data analysis and statistical modeling.
• Data Visualization: Experienced in using tools like Tableau, Power BI, and Matplotlib/Seaborn for creating compelling visualizations.
• Database Management: Knowledgeable in SQL for efficient data retrieval and management.