PRIYANKA BADGUJAR

• Developed AI-driven data pipelines integrating event and e-commerce data (Eventbrite, Etsy, eBay) into structured datasets for analytics and model training.
• Designed and evaluated LLM prompts, assessing correctness, clarity, and contextual accuracy to improve reasoning quality in AI outputs.
• Conducted annotation, classification, and similarity evaluations, refining AI datasets and ensuring alignment with project guidelines.
• Built a Power BI dashboard combining structured KPIs with AI-generated insights, enhancing visibility into engagement and model accuracy.
• Automated data preprocessing and reporting workflows using Python scripts and REST APIs, reducing manual effort and improving reporting efficiency.

• Automated data extraction pipelines using Python (Selenium, BeautifulSoup) for YouTube content analytics across 20+ channels (2,500+ videos).
• Applied classification and regression models to predict audience engagement and content preferences.
• Classified recipes based on ingredients, popularity metrics (views, likes, comments), and audience engagement patterns to identify high-performing content. Applied linear regression to predict user preferences, generating tailored recipe suggestions for improved engagement.
• Designed interactive Tableau dashboards (bar charts, pie charts, scatter plots) to visualize high-performing content trends and support business strategy.

• Conducted exploratory data analysis, feature selection, and relevance checks to enhance model reliability. Built interactive dashboards in Tableau to visualize trends and provide actionable recommendations.
• Managed PostgreSQL and MongoDB databases, ensuring structured, accessible datasets for analysis and AI workflows.
• Developed and evaluated ML models (scikit-learn, XGBoost), validating output accuracy and factuality. Created and tested RESTful APIs for AI model integration, enabling efficient data exchange between components.
• Used AWS for distributed computing and large-scale data processing. Collaborated with QA teams on unit and A/B testing, bug tracking, and reporting to maintain software quality.