sudhanshu.kulkarni50
FeaturedAbout Candidate
Data Analyst with hands-on experience in SQL, Python, and cloud-based ETL pipelines, delivering analytics-ready datasets and business dashboards. Proven ability to translate raw data into actionable insights across operations, inventory, and governance use cases.
Location
Education
A graduate of Shivaji University with a BTech in Computer Science, I have a solid foundation in database management and data analytics. My educational background and prior experiences with tools like SQL, Power BI, and Excel have equipped me to assist organizations in making informed decisions and enhancing efficiencies. Striving for excellence, I seek to create meaningful impacts through innovative data solutions.
Work & Experience
Built and maintained SQL-based data transformation layers for 15,000+ operational records, supporting analytics and reporting needs. Standardized and cleaned data across multiple source systems, reducing recurring data quality issues. Optimized SQL queries powering Metabase dashboards, improving query performance and data freshness. Defined data models, KPIs, and reporting metrics in collaboration with stakeholders to ensure reliable downstream consumption. Created weekly and monthly hiring analytics reports to track recruitment trends and operational performance. Conducted virtual training sessions for clients and internal teams, explaining dashboards, metrics, and resolving data-related queries. Acted as a data partner to business teams, translating hiring requirements into actionable insights.
Cleaned and transformed AFDC material datasets using SQL and Excel to support inventory and procurement systems. Prepared structured and validated datasets for Power BI dashboards used by operations and supply chain teams. Supported KPI tracking and reporting for stock movement, vendor performance, and material usage. Assisted in defining data structures, validation rules, and data quality checks for inventory monitoring workflows. Automated SAP Order-to-Cash (O2C) processes including Quotations, Purchase Orders, and Invoices within the SAP SD module, improving process efficiency. Streamlined employee operations using SAP Time Manager Workplace to enhance time tracking and operational control. Built automated workflows using Power Automate and executed Python scripts to process and highlight specific documents, improving document handling accuracy and turnaround time.
Built an AI-driven project titled “Automate Sentiment Analysis of Textual Comments and Feedback” to support data-driven decision-making. Collected, cleaned, and preprocessed large volumes of textual data to prepare for model training and evaluation. Deployed Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN) to enhance sentiment classification accuracy. Improved the reliability and efficiency of sentiment insights, contributing to more informed business analysis.
