Chavi Pathak

• Partnered with Auzmor on strategic LMS implementations and client engagements, translating evolving business needs into scalable product requirements and execution plans. • Led end-to-end strategy and execution of 5+ product features, owning PRDs and partnering with engineering and UI/UX teams to reduce manual workflows by 30% and accelerate release cycles. • Drove cross-functional collaboration across design and engineering to improve onboarding and navigation flows, delivering an 18% uplift in user adoption and engagement. • Defined product success metrics and executed A/B tests on UI enhancements, translating insights into prioritized backlogs and measurable engagement gains. • Built SQL and Power BI dashboards to monitor feature usage, retention, and churn drivers, enabling data-informed decisions that reduced churn by 12%. • Led UAT, stakeholder alignment, and RFP solution mapping to ensure scalable, user-centric product delivery aligned with business objectives. • Delivered product and analytics solutions for government and higher-ed clients, including Utah Valley University (UVU), Madison Metropolitan Sewerage Authority, aligning technology initiatives with environmental and institutional objectives.

• Developed and automated an HR data processing system using SQL, Python, Hadoop, and Power Automate, significantly reducing manual data entry and processing time. • Designed and deployed Tableau and Excel dashboards, enhancing HR analytics visibility for multiple stakeholders and improving operational efficiency. • Led an Agile project team in developing an automated HR system for subsidiaries, streamlining client acquisition processes through iterative development and continuous collaboration. • Conducted A/B testing on HR data workflows to optimize data validation processes and enhance client acquisition strategies.

• Integrated multi-source retail data into AWS Redshift, establishing a unified data warehouse for real-time analysis of customer transactions and purchasing patterns. • Visualized consumer behavior trends by curating interactive Power BI dashboards with actionable KPI scorecards, facilitating data-driven marketing decisions. • Applied advanced DAX formulas to create custom calculations for marketing segmentation, optimizing targeted marketing strategies. • Utilized NetSuite's ad hoc reporting capabilities to generate on-demand financial and operational reports, enabling swift decision-making and reducing reliance on pre-defined templates.

1)Developed predictive models using Python (Logistic Regression, Collaborative Filtering) to analyze customer behavior and drive predictive analytics, enhancing marketing strategy effectiveness by 20%. 2)Engineered scalable ETL pipelines with SQL and Python, ensuring high data integrity and reducing processing time, which improved the delivery of high-quality datasets for strategic data analysis and reporting. 3)Leveraged NLP and statistical analysis for sentiment analysis to extract actionable insights, influencing product operations and refining marketing and product strategies. 4)Collaborated in an Agile environment while managing multiple projects simultaneously; utilized Microsoft Excel, Pandas, and Flask for dynamic data visualization, capacity planning, and comprehensive business analysis.

1)Developed interactive dashboards using Microsoft Excel, Tableau, and Microsoft Power BI to track product performance and market trends, applying robust market research and marketing strategy skills. 2)Conducted detailed data analysis and cleaning with Microsoft Excel and Power BI, streamlining product operations and enabling informed decisions through strong management and analytical skills. 3)Collaborated with cross-functional teams by leveraging Microsoft Word for documentation and communication, ensuring project alignment and enhancing overall management effectiveness

1)Engineered and optimized ETL pipelines using SQL and Python to ingest, cleanse, and integrate data from multiple sources into AWS Redshift, ensuring high-quality datasets for comprehensive business analysis. 2)Developed interactive dashboards with Power BI, Tableau, and Qlik, leveraging AWS Redshift for centralized data warehousing to drive data-driven decision-making and effective remote collaboration.

1)Led the research project “Big Data Analytics for Chronic Disease Prediction,” utilizing R, SQL, and Python to build predictive analytics models and conduct comprehensive data cleaning on large-scale healthcare datasets. 2)Collaborated with VIT faculty to refine research methodologies and leverage advanced predictive analytics, resulting in actionable insights and publication in the International Journal of Modernization in Engineering Technology and Science (IRJMETS).

Subjects - Principles of Marketing, Business databases and design , Statistics for Data Science.

Courses: DBMS, OS, Information Systems Management, Information security audit and analysis, Total quality Management(TQM), Cyber security, Technical Solutions to Real World problems( TARP), Cryptography, Software Engineering