Surya Prakash Reddy Gouni
About
Detail
Data Analyst with expertise in Python, and Data Visualization using Power BI, MS Excel
United States
Résumé
Jobs
verified_user
0% verified
Data Analyst- Special educationBaltimore City Public SchoolsMar 2025 - Current (1 year 7 months)• Support strategic use of special education data by assembling, cleaning, and managing large datasets to ensure accuracy in performance management and compliance reporting. • Develop and implement project plans including timelines, KPIs, and communication strategies to inform district and school-level decision-making. • Create and maintain daily, monthly, and quarterly reports using Power BI and Excel, ensuring timely and accurate data validation across schools. • Conduct data analysis using Python and R to identify trends, challenges, and areas for improvement, supporting targeted interventions and policy updates. • Design custom reports and simplified queries using SQL and Power Query to address systemic data management issues and e- Data AnalystMedStar HealthJul 2024 - Feb 2025 (8 months)• Collaborated with cross-functional teams in Agile environments to gather requirements and build TensorFlow based predictive models that improved patient are and increased efficiency by 30%. • Automated data extraction, transformation, and reporting processes using Python, Alteryx, and PostgreSQL, increasing workflow efficiency by 40%, ensuring data integrity, and supporting advanced analytics. • Built comprehensive Power BI dashboards to visualize healthcare metrics, defined KPIs with stakeholders, and trained 50+ team members on effective data interpretation. • Leveraged Azure Cloud for secure data storage and optimized analytics workflows, improving scalability and performance by 25%. • Led JAD sessions to align data initiatives wi
- Data AnalystAccentureJun 2020 - Jul 2022 (2 years 2 months)• Developed robust Python scripts for seamless extraction, transformation, and automation of financial workflows, reducing reporting time by 35% and enhancing SQL query precision through rigorous validation. • Used NumPy for advanced computations and Pandas to clean, aggregate, and analyze spending and revenue trends, boosting data processing efficiency by 40%. • Designed interactive Tableau dashboards to visualize financial insights, collaborate on KPIs, and deliver training to 30+ stakeholders on best practices, improving decision-making speed by 25%. • Deployed scalable Azure Cloud solutions to optimize resources and enhance project scalability, reducing infrastructure costs by 20%. • Conducted hypothesis testing and regression anal
Education
verified_user
0% verified
- Master of ScienceUniversity of Maryland Baltimore CountyAug 2022 - May 2024 (1 year 10 months)
- MBachelor of Technology (B. Tech)Malla Reddy College of Engineering and TechnologyMay 2022 - Jun 2025 (3 years 2 months)
- DData Visualization: IBM
- AAzure AI Fundamentals: Microsoft
Projects (professional or personal)
verified_user
0% verified
- DDETECTING COVID-19 AND PNEUMONIA FORM CHEST X-RAYS USING DEEP LEARNING AND MACHINE LEARNING• Gathered a huge collection of chest X-Rays from accessible databases • Utilized Convolutional Neural Networks (CNNs) for their efficiency in image recognition • Leveraged VGG- 16 is the foundational model for feature extraction due to its superior classification accuracy, enhancing predictive performance of the system by 25% and reducing error rates by 15%.
- FFLIGHT DELAYS ANALYSIS AND PREDICTIONS• Improved predictive accuracy by 98% with decision tree and linear regression models, enhancing operational efficiency. Streamlined repetitive processes, reducing manual intervention through pipelining • Reduced resource allocation errors by 20% by predicting flight delays, optimizing scheduling and customer satisfaction. • Streamlined ETL processes with MongoDB pipelines, cutting data processing time by 50% and improving model input efficiency by 30%.
- PPREDICTING CUSTOMER SUBSCRIPTION TO PERSONAL LOAN OFFERS• Cleaned and prepared data, addressing missing values and feature engineering for high-quality model input. • Engineered a logistic regression model, improving accuracy by 18% over random forest and decision tree on 20,000+ records. • Created Power BI dashboards, increasing decision-making efficiency by 40% and reducing report time by 50%. • Developed a logistic regression model for a STREAMLIT app, boosting user engagement and retention by 40%.