Built ETL pipelines with PySpark to integrate 50K+ housing prices records from 2 data sources, reducing data extraction errors by 30%

Implemented robust data cleaning, preprocessing, and exploratory data analysis to draw meaningful insights for further evaluation and model creation

Coordinated analysis of 2008 recession & COVID19 impact by optimizing time series models (ARIMA, SARIMAX, LSTM) for precise housing price predictions and trend analysis, achieving a 25% decrease in error metrics (RMSE, MEA) compared to regression models

Crafted a Tableau story and demonstrated model performances, insights & recommendations to senior management

Administered requirement analysis, created, managed, and conveyed product backlog and user stories in product meetings using storyboards, resulting in process improvement and efficiency hike by 20%

Orchestrated re-sampling methodology to increase user retention rate, employed data modeling to formulate pricing strategies and identify strategic partners, resulting in a 30% network expansion for the client: facilitating 25% increase in Global market penetration

Proactively managed requirements and facilitated change through qualitative & quantitative data analysis, interviews, and surveys

Leveraged Power BI for user behavior analysis, shaping marketing strategies, resulting in a 20% boost in customer acquisition

Spearheaded market research/analysis, thereby creating situation statements and project roadmaps, guiding to successful product launch

Employed elicitation techniques, managed requirements, and maintained traceability, driving alignment with business goals

Established a plan to create SQL database, accelerating customer data access, analysis, and retrieval by 30% for improved product development and visualized the Key Performance Indicators (KPIs) in Excel and Tableau to recommend solutions for identified business requirements

Worked with university’s dining services to strategically design their menu with an ultimate goal of reducing greenhouse gas emissions and calories intake by 70% by 2030

Defined functional requirements for analytics and business intelligence (BI) solutions, created product roadmap & user stories, analyzed and validated data with statistical analysis (Excel, R) and data visualization (Power BI) and reported to stakeholders for university-wide strategic initiatives 

 Built an application with PowerApps for UMD’s dining services to track food-related greenhouse gas emissions

Created a data analysis framework with Excel, R, and Power BI. Presented insights, guiding university strategies and projecting ~8% CO2 emissions drop in 8 years 

Led Azure Percept DK delivery (600+ global partners) with cross-functional teams for User Acceptance Testing, maintained performance metrics, measurements, methods, and targets, and examined trends to evaluate operational efficiency

Engineered a robust SQL database structure for analyzing and consolidating 50K+ transactional records; executed data cleaning protocols and optimized SQL queries, resulting in a 70% reduction in errors, enhancing accuracy for profitability analysis

Collaborated with UX and development teams for software testing, studied feedback, identified improvements using root cause analysis, adhered to the SLA, thereby enhancing product development, and yielding a 30% increase in application efficiency and responsiveness

Developed 10+ Power BI dashboards with DAX for data modeling, unifying sources for cross-domain analytics & insights 

Analyzed the customer feedback data using Sentiment Analysis (NLP and Python) to understand needs of rural customers

Identified the demand for data preprocessing to enhance the quality and effectiveness of analysis processes, performed text preprocessing (tokenization, stemming, stop-word removal, POS tagging) enhancing data analysis and insights

Usage of Jio mobile phones rose by 20% in rural areas with appropriate resource allocation and sales and marketing efforts