V
Vasavi Rayala
About
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Overland Park, Kansas, United States
Résumé
Jobs
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- BGen AI EngineerBlue Cross and Blue Shield of KansasJul 2024 - Current (1 year 10 months)Architected a comprehensive AI system to monitor patient adherence, providing real-time risk scores and automated clinical insights, enabling care teams to proactively support high-risk patients and improve treatment outcomes. Implemented predictive adherence models using Python, SQL, PyTorch, and Hugging Face Transformers, leveraging CNN-Transformer architectures to boost prediction accuracy by 24% and reduce false-positive alerts by 17%. Orchestrated scalable data pipelines with Apache Spark and MLflow to process longitudinal EHR, pharmacy, and behavioral datasets, improving throughput by 31% and shortening model retraining cycles by 28%. Devised NLP pipelines using Text Generation and NER to extract medication instructions, refill deviat
AI/ML EngineerAccentureJul 2022 - Jul 2023 (1 year 1 month)Engineered predictive models with TensorFlow and Scikit-learn to forecast market trends, enabling data-driven asset allocation and improving portfolio performance by 5% under volatile market conditions. Simulated Monte Carlo scenarios across 7,500 portfolios, reducing portfolio risk by 3% and increasing expected returns by 4% through optimized asset distribution strategies. Configured Bayesian Optimization to identify optimal asset combinations across diverse risk-return scenarios, enhancing portfolio efficiency and improving risk-adjusted returns by 3%. Constructed a hybrid optimization framework with Genetic Algorithms for diversification and Reinforcement Learning for dynamic asset rebalancing, boosting returns by 6% and reducing portfol- Data ScientistInfosysJan 2021 - Jul 2022 (1 year 7 months)Spearheaded development of an enterprise AI platform to accelerate banking AI adoption, integrating predictive modeling, NLP, time-series forecasting, and anomaly detection, optimizing customer experience across 5+ banking units. Established and deployed a ticket classification engine using Natural Language Processing, TF-IDF, and supervised models, automating B2B ticket triage, reducing manual effort by 40%, and improving response accuracy by 35%. Leveraged time-series forecasting pipelines with ARIMA and Statsmodels to predict support resolution delays, enabling proactive workload management and reducing escalations by 22% across 12,000+ monthly support tickets. Developed topic modeling (LDA) and semantic similarity frameworks to extract
Education
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- MMicrosoft Certified: Azure AI Engineer AssociateFeb 2025 - Mar 2025 (2 months)
- AAWS Certified Machine Learning specialtyOct 2024 - Nov 2024 (2 months)
- WMaster of Science in Information Technology and ManagementWebster University, St-LouisAug 2023 - Mar 2025 (1 year 8 months)MO, USA
- DBachelor of Technology in Electrical and Electronics EngineeringDvr & Dr. Hs Mic college of TechnologyAug 2019 - Apr 2023 (3 years 9 months)AP, India
Projects (professional or personal)
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- FFinancial Time-Series ForecastingAug 2024 - Nov 2024 (4 months)Designed an LSTM model with TensorFlow/Keras to predict stock trends with real-time API inference. Conducted feature engineering on multivariate financial data (price, volume, volatility), improving forecast RMSE by 12%. Provisioned model via Flask API and visualized performance using Matplotlib and Plotly dashboards for decision support.
- CChatbot with RAG using OpenAI + PineconeMay 2024 - Jun 2024 (2 months)Created a RAG chatbot using GPT-4, LangChain, and Pinecone for context-aware, domain-specific responses. Applied embedding-based semantic search with FAISS/Pinecone, improving retrieval precision by 25%. Released the solution via FastAPI on AWS, enabling scalable and low-latency interaction across multiple user sessions.
- HHealthcare Predictive Analytics SystemMay 2023 - Jun 2023 (2 months)Built an end-to-end ML pipeline with Python, PyTorch, and AWS SageMaker to predict patient risk scores from clinical data. Automated data preprocessing and model deployment with AWS Lambda and MLflow, improving prediction accuracy by 18% and reducing manual data handling by 30%. Integrated Power BI dashboards for real-time visualization of health insights and predictive outcomes.