I am a versatile interdisciplinary Data Scientist and Statistician with a unique skill set in statistical modeling, data analysis, and modern ML/DevOps practices. Over the course of my professional career, I have had the privilege to contribute meaningful, production-focused solutions across industry and academia.
With hands-on experience deploying and maintaining machine learning systems, I have developed and supported data-driven methods and software solutions for both the energy sector and B2B marketplace environments. My recent work includes maintaining lead-scoring and customer health–scoring pipelines, ensuring model reliability, data quality, and commercial impact for sales and customer success teams. My broader expertise lies in implementing predictive analytics workflows, optimization strategies, and scalable data pipelines that enhance statistical efficiency and operational value.
As a data science researcher, I focused on infectious disease analytics, developing statistical models and tools tailored to the needs of scientists and public health agencies. My goal as a data scientist is to harness the potential of data-driven solutions to transform complex data into actionable knowledge and measurable value.