S Cherukuri Email & Phone Number

United States

• Analyzed company financial information, conducted market research for budget planning, and forecasted profit in Excel, presenting analysis reports to senior management for decision-making.
• Developed and implemented data pipelines using Azure Data Factory, resulting in a 50% reduction in processing time for data flows in and out of data storages.
• Conducted efficient meetings, articulating recommendations, and solutions to stakeholders, and communicated default customer profiles along with reports using Tableau, presenting analytical results and strategic.
• Built out data and reporting infrastructure from the ground up using Tableau and SQL to provide real-time insights into product, marketing funnels, and business KPIs.
• Reduced operational costs by 19% through research into multiple information sources and successful root cause analysis of production and performance problems.
• Used SQL, Tableau, and Cloudera to compile monthly 40+ page summaries of company operations, identifying key areas for improvement for senior management.

Bangalore Urban, Karnataka, India

• Utilized Power BI to conduct in-depth data analysis, leveraging its features to create comprehensive data models.
• Developed dynamic dashboards, detailed reports, and paginated reports tailored for business users’ needs.
• Leveraged SAS for advanced data manipulation and analysis, enabling deeper insights into data trends andpatterns.
• Assisted in creating and executing SAS scripts for data processing and quality checks, ensuring data accuracy.
• Led the process of gathering business requirements, conducting thorough analysis, and proposing effective solutionsand designs.
• Worked collaboratively to ensure alignment with stakeholders and successfully implemented solutions.

India

• Spearheaded a data-driven property pricing optimization project in a Prop Technology company, utilizing Python, Scikit-learn, and Power BI for comprehensive analysis.
• Gathered and pre-processed extensive real estate data, including property attributes, historical sales, and market trends.
• Leveraged Pandas and NumPy libraries for efficient data manipulation and Scikit-learn for advanced regression modeling.
• Successfully achieved a 20% reduction in Mean Absolute Error (MAE), significantly enhancing price prediction accuracy.
• Created insightful and interactive data visualizations in Power BI, enabling stakeholders to make informed decisions regarding pricing strategies.
• Empowered the team with actionable market insights and pricing patterns to drive strategic decision-making.

Master'S Degree, Computer Science, 3.3

Bachelor'S Degree, Computer Science