Akansh Singh Rathore

Conducted comprehensive statistical analysis of continuous, categorical, and ordinal data for thesis and PhD studies, utilizing IBM SPSS to derive robust insights.

Developed and presented compelling data visualizations, including tables and graphs, to effectively communicate complex statistical findings from surveys.

Designed and executed hypothesis testing protocols to validate research assumptions, contributing to evidence-based decision-making for academic and research papers.

Optimized data interpretation and reporting processes through effective application of SPSS, enhancing the clarity and impact of research conclusions.

Performed statistical analysis on continuous, categorical, and ordinal datasets for academic theses and research papers, leveraging SPSS tools for data interpretation.

Generated detailed tables and graphs to visualize complex data trends, facilitating clearer understanding and presentation of research findings.

Assisted in developing and testing hypotheses for survey data, contributing to the derivation of actionable insights for research projects.

Gained practical experience in data cleaning, transformation, and statistical reporting, enhancing foundational data analysis skills.

Mastered advanced data analysis techniques and statistical concepts through a rigorous bootcamp, building a strong foundation in data science.

Developed proficiency in key data tools including Advanced Excel, PowerBI, Tableau, Python, MySQL, R, and SAS for data manipulation, analysis, and visualization.

Applied learned analytical skills to simulated real-world datasets, solving complex problems and deriving actionable insights.

Cultivated a comprehensive understanding of the data lifecycle, from data acquisition and cleaning to analysis and reporting, preparing for professional roles.

Operated Marg ERP software to integrate and manage daily accounting, inventory, and sales processes, enhancing operational cohesion.

Streamlined financial record-keeping, reducing manual errors and improving data accuracy for critical business reporting.

Maintained precise inventory levels and sales data, providing reliable information for procurement and sales forecasting decisions.

Contributed to informed decision-making by ensuring timely and accurate data availability across key business functions.