Varsha Ramesh

• Spearheaded pivotal project to enhance Visual Care software's reporting capabilities.
• Orchestrated extraction of vital data from Visual Care and Medicare databases for detailed analysis.
• Utilized Python for precise data cleaning and manipulation, implementing advanced techniques for accuracy and consistency.
• Expertly harnessed Python libraries, such as Pandas, NumPy, and Scikit-learn, for data preprocessing, imputing missing data, and detecting outliers.
• Designed and implemented a robust reporting system using Python's data visualization libraries like Matplotlib and Seaborn, delivering insightful client reports.
• Reports offered comprehensive insights into Resource Allocation, Budget Management, and Quality of Care Monitoring for individual clients.
• Optimized Resource Allocation, including caregiver, medical equipment, and transportation services, utilizing regression analysis.
• Ensured efficient Budget Management for clients receiving financial support, tracking expenses, and preventing overruns.
• Improved service quality through data-driven Quality of Care Monitoring, employing statistical methods and hypothesis testing.
• Proficiently utilized JIRA for effective project management, task allocation, progress tracking, and team communication.

Clients: Traffic Guard, Open Money, Chai Finance, Flight Centre Management, Living Edge.

Projects

Looker Developer/Consultant

• Gathering and comprehending business requirements through interaction with clients and prospects.
• Analyzing use cases for diverse customer teams.
• Creating logical data models, charts, reports, and dashboards based on client data analysis.
• Developed, designed, and supported interactive dashboards and reports depending on client requirements.
• Provided production support for Looker dashboards and reporting solutions along with performance tuning.
• Supported the creation of project prototypes and iterations.

Data Management Specialist (ETL/ELT)

• Facilitated and coordinated discussions to manage the expectations of multiple stakeholders.
• Processing and scheduling monitoring and management (including ETL/ELT) for projects.
• Providing break-fix support for operating projects as required and for ad hoc and unscheduled data sources, manual data loading is required.
• Managing support tickets, troubleshooting, and escalation.
• Managing and handling data pipeline using PDI (Pentaho Data Integration) and Cloud Connect.
• Handling migration of the database from Postgres to Google BigQuery, which reduced dashboard reload time.
• Usage of Google Cloud products such as GCS, BigQuery, and Virtual Machines for data warehousing and data pipelines.