Rishika Ravi Kukuttala

• Collected data from databases, APIs, and external sources; performed cleaning and validation to ensure high data accuracy and reliability for analysis. • Applied statistical methods and built predictive models (regression, clustering, Python, scikit-learn) to uncover trends, forecast outcomes, and support strategic decision-making. • Developed impactful dashboards and reports using Tableau, Power BI, and Excel to communicate insights effectively to both technical and non-technical stakeholders. • Worked closely with teams such as marketing and finance to translate business needs into data-driven solutions, improving processes, identifying efficiencies, and highlighting revenue opportunities. • Ensured compliance with GDPR/CCPA, maintained strong data governance practices, and monitored key performance indicators (KPIs) to track progress and guide organizational strategy.

-Engineered a modular AI-powered document processing pipeline using LangChain, FAISS, and efficient LLM models, improving document retrieval accuracy by 40%. -Automated data ingestion, text extraction, semantic embeddings, and context-aware querying, reducing research workflow time by 50%. -Implemented RAG architecture for natural language questions answering across large unstructured document sets. -Optimized vector search and inference latency, improving real-time retrieval performance and scalability for multimodal AI use cases. -Developed Langflow dashboards for visualizing LLM responses, enabling transparent debugging and workflow optimization.

-Built ETL data pipelines for structured and unstructured sources using Python (Pandas, NumPy) and SQL, enhancing data integration and accuracy. -Designed Power BI dashboards and interactive Excel reports to visualize KPIs, operational metrics, and sales trends, enabling data-driven decision-making. -Applied forecasting models and regression analysis to predict business growth patterns, achieving a 15% improvement in demand forecasting accuracy. -Collaborated cross-functionally with finance and operations teams to implement data quality controls and improve reporting timeliness.

-Analyzed UAV telemetry and operational data using Python and SQL, improving performance insights by 25%. -Integrated AWS-based data pipelines into CI/CD workflows, increasing reporting reliability and speed by 40%. -Automated data workflows and reporting processes, reducing manual effort by 30%. -Enhanced data accessibility through PostgreSQL and AWS integration, supporting faster design and operational decisions.