Guna Yaswanth Gadde
Professional Summary
Data Analyst with 0 years of professional experience leveraging Python, SQL, Power BI and machine learning to clean, analyze and visualize complex datasets. Strong foundation in building data pipelines, creating interactive dashboards, and applying ML models to solve business and healthcare problems; proven ability to convert data into actionable insights for cross-functional teams.
Technical Skills
Work Experience
- Executed detailed image annotation and labeling tasks following structured guidelines to prepare training data for computer vision models, ensuring consistent metadata and label quality across datasets.
- Performed multi-stage validation and evaluation of annotated images to identify inconsistency and edge cases, improving dataset reliability for downstream model training.
- Documented annotation guidelines and created quality checklists to standardize labeling practices across contributors, increasing annotation consistency.
- Collaborated with cross-functional teams (data scientists and product leads) to address data gaps and refine annotation rules to align datasets with model requirements.
- Applied data security and confidentiality best practices when handling sensitive image data, maintaining compliance with project policies and ethical standards.
- Provided feedback loops to labelers and modelers by reporting common error patterns and suggested corrective actions to enhance dataset quality over iterative cycles.
- Reviewed and approved 500+ job postings weekly on the Handshake platform, enforcing compliance and accuracy to protect student applicants and maintain platform integrity.
- Analyzed student employment and engagement datasets using Excel and Tableau to identify hiring trends and present action-oriented insights to career services staff.
- Generated recurring performance and engagement reports for students and employer partners, enabling data-driven decisions that improved placement outreach.
- Coordinated large career events (Tech Fest, Spring Fest) serving 200+ employers and 3,000+ students, using data tracking to optimize employer-student matching and event logistics.
- Built interactive dashboards and visualizations to track job categories, employer engagement, and student application behavior for leadership reporting.
- Maintained data quality by auditing job-posting metadata and resolving discrepancies between platform records and internal databases.
- Monitored production data systems across PostgreSQL and Snowflake environments, identifying performance bottlenecks and ensuring data availability for business reporting.
- Investigated system incidents via log analysis and root-cause troubleshooting, contributing to a 35% reduction in incident-related downtime for supported systems.
- Optimized SQL queries and applied indexing strategies to improve database responsiveness, resulting in an 18% performance improvement for key reporting queries.
- Automated operational reporting workflows with Jenkins CI/CD to streamline deployments and ensure consistent monitoring across environments.
- Collaborated with cross-functional engineering and operations teams to maintain uptime SLAs and implement reliability improvements for client systems.
- Prepared operational documentation and incident reports to support knowledge transfer and continuous improvement of support processes.
- Developed a web-based medical diagnostic interface using HTML, CSS and JavaScript to collect patient inputs and present model predictions in a clinician-friendly format.
- Integrated a machine learning model into the diagnostic tool to predict diseases from patient inputs, enabling faster preliminary assessments for healthcare staff.
- Implemented frontend data validation and client-side preprocessing to ensure clean input for ML model inference and reliable user interactions.
- Collaborated with domain stakeholders to translate clinical requirements into functional features and iteratively refine the diagnostic workflow.
- Tested and validated model outputs against sample clinical cases to identify misclassification patterns and inform model improvement efforts.
- Documented development work and assisted in demonstrations to internal users, supporting adoption and feedback collection for product iteration.
Education
Certifications
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