Saisunil Garlapati

- Designed and implemented machine learning models for evaluating clinical data, improving product offerings and service delivery.

- Developed Python applications for data manipulation and visualization, enhancing reporting processes and stakeholder engagement.

- Conducted data analysis using SAS and Tableau to identify trends, presenting findings to stakeholders with clarity and confidence.

- Executed comprehensive data wrangling and ELT processes to manage large datasets, ensuring data quality and availability for analysis.

- Built Power BI visualizations and dashboards to monitor key performance indicators, facilitating data-driven decision-making.

- Collaborated with business stakeholders to define metrics for model evaluation and developed repeatable experiments for assessment.

- Predicted sales opportunities from account and sales data using Python in Azure Databricks, achieving an 85% cross-validation accuracy in identifying viable sales conversions using Random Forest Classifier (RFC) and Multi-Layer Perceptron (MLP).

- Conducted exploratory data analysis to identify key factors influencing sales opportunity conversion.

- Developed a regression model in Azure to forecast quarterly sales conversions and revenues, utilizing analytical strategies to drive business insights.