• Employed machine learning classification algorithms, including Random Forest and k-NN, to analyze and categorize collegesbased on doctoral degree conferral data (2019–20) and faculty counts (Fall 2020) from IPEDS, resulting in improvedinstitutional insights.• Successfully classified institutions into R1, R2, and R3 research activity levels, contributing to enhanced strategic positioningof the university among leading research institutions.• Leveraged Principal Component Analysis (PCA) on NSF fiscal year 2020 research and development datasets to derive insightsthat enhanced strategic decision-making and significantly improved the university’s R1 ranking.• Developed and implemented machine learning models in Python to preprocess and analyze complex datasets from QS News,US News, and other educational rankings, enhancing predictive accuracy for university rankings and research output.• Achieved a 30% reduction in manual data processing time by automating data analysis workflows, significantly improvingefficiency in handling large-scale educational datasets.• Designed and implemented a dynamic dashboard using MicroStrategy and Python, integrating machine learning models toprovide real-time insights and predictive analytics for university leadership.• Created visualizations that empowered stakeholders with data-driven strategies, facilitating informed decision-making andidentifying key areas for improvement within the institution.• Fine-tuned NLP models to analyze unstructured data from surveys, academic papers, and research profiles, deliveringsentiment analysis and text summarization that generated insights to enhance the university's academic standing.

Designed and optimized high-performance backend services utilizing Linux, Informix 4GL, and MS SQL, significantlyenhancing scalability and performance for 10+ end-to-end applications.• Created dynamic reports and dashboards in MS Excel and Power BI, delivering impactful data visualizations and key insightsto clients for informed decision-making.• Authored SOPs to streamline project migration, mitigating errors and enhancing communication during critical transitions,while managing databases in Linux (MySQL) and Windows (MS SQL Server).• Managed and supported 10+ applications across various platforms, ensuring business continuity by adhering to SLAs,monitoring server health, managing user permissions, and deploying code and packages.• Extracted and analyzed data using ServiceNow and SQL, and built custom dashboards and predictive models (e.g., RandomForest) in Python to identify issues and enhance decision-making.• Automated daily monitoring and server maintenance tasks with Linux scripts, reducing manual efforts by 60%, and provideddetailed reports to clients, supporting business growth.• Led and mentored junior engineers, fostering a data-driven culture and collaborating across teams for change deployments,server migration, and project improvements.

I was working as a sales intern, developing knowledge on sales industry.