Rishidhar K Email & Phone Number

Tampa, Florida, United States

As a Senior Data Scientist at WellCare, I design and implement end-to-end healthcare analytics solutions using GCP (BigQuery, Vertex AI) and AWS (SageMaker, Redshift), focusing on patient monitoring, disease prediction, and marketing analytics. I've developed predictive models for diagnosis and treatment planning, integrating NLP with PySpark and GPUs, achieving 95% accuracy in complex time-series data. By applying Generative AI (GAN-based) solutions, I enhanced patient education content, improving engagement by 25%. My work in fraud detection using Hadoop algorithms strengthened data security, while automated MLOps practices streamlined model retraining. Notably, I led a project that reduced customer churn by 30% and boosted acquisition by 20% through data-driven insights, aligning technical solutions with business objectives.

Bothell, Washington, United States

As a Data Scientist at CVS Health, I led the development of predictive models that drove a 20% improvement in early intervention strategies and hospital resource allocation. I enhanced fraud detection in medical billing by reducing false positives by 30% using anomaly detection on GCP. I utilized Apache Spark to build scalable patient segmentation models, reducing readmissions by 15%, and leveraged deep learning (TensorFlow, PyTorch) to improve diagnostic accuracy by 25%. I also integrated LLMs into healthcare chatbots, significantly improving patient satisfaction. By orchestrating AI/ML pipelines on GCP and Azure, I accelerated real-time patient data analysis, reducing deployment times by 40%. My work also spanned applying computer vision for medical image analysis, developing clinical trial optimization models, and enhancing healthcare investment analysis with Generative AI. These efforts contributed to more efficient operations, reduced costs, and improved patient outcomes.

New York, United States

As a Data Scientist at AIG, I led initiatives to improve underwriting accuracy and risk management by developing machine learning models with XGBoost and Random Forest, achieving a 25% improvement in underwriting precision. I implemented clustering techniques for customer segmentation, enhancing the targeting of personalized insurance products. My work in fraud detection, utilizing anomaly detection on GCP, reduced false positives by 30%. I applied time series analysis models like ARIMA and Prophet to forecast claims frequency, optimizing resources. I developed dynamic pricing strategies that improved pricing accuracy by 20%, and leveraged NLP models like BERT and spaCy for better claims classification and sentiment analysis. Additionally, I built deep learning models for risk prediction and created ETL pipelines with Apache Spark and Kafka to streamline data processing. My contributions also included fraud detection via graph-based methods, reducing fraud incidents by 35%, and implementing real-time Azure analytics for KPI tracking, reducing reporting times by 40%. I supported strategic decision-making with Tableau dashboards and improved customer satisfaction by forecasting asset maintenance needs.

India

India