Data Analyst
Current• Created and managed complex Excel workbooks, employing advanced functions such as pivot tables, VLOOKUP, HLOOKUP, and macros to streamline the organization, analysis, and visualization of clinical data. • Designed and maintained relational databases using SQL, optimizing data storage, retrieval, and management of clinical records to ensure data integrity and accessibility. • Complied complex SQL queries and stored procedures to extract, manipulate, and analyze data, supporting clinical research and operational decision-making. • Leveraged Python libraries such as Pandas, NumPy, and SciPy to perform data cleaning, transformation, and analysis on large datasets, uncovering actionable insights and trends in patient care. • Automated routine data extraction and reporting processes using Python scripts, enhancing efficiency and consistency in data management tasks. • Applied R programming for statistical analysis and data modeling, conducting predictive analytics to identify patterns and potential risk factors in patient records. • Generated comprehensive statistical reports and visualizations, aiding clinical teams in developing evidence-based treatment plans and interventions. • Designed interactive Power BI dashboards to visualize key performance indicators (KPIs) and clinical metrics, providing real-time insights to healthcare providers and administrative staff. • Integrated data from multiple sources into Power BI, creating cohesive and dynamic visualizations that support strategic decision-making and performance monitoring. • Conducted regular data quality assessments and data cleansing activities. • Ensured compliance with HIPAA regulations and other industry standards in all data management and reporting activities, protecting patient privacy and maintaining data security. • Collaborated with clinical and IT teams to develop and refine data collection protocols and reporting standards, improving data consistency and usability across the organization.