I am a strong R programmer with experience applying big data tools and machine learning methods to deliver actionable insights to senior business leaders and stakeholders. As a senior data scientist at AT&T, I collaborated with senior business leaders and a diverse technical team to identify opportunities for retail optimization. I designed a pilot study to test proposed solutions in the field and created visualizations to communicate study performance metrics to senior business leaders and the technical team. I also developed and validated classification models using machine learning algorithms, applying knowledge of big data tools for data acquisition/manipulation (R, SQL) and data analysis (Hadoop, Hive, Spark, H2o).
I have over 7 years of technical experience at two highly regarded scientific research institutions known for important advances in many areas, including national security, supercomputing, and biomedical discoveries. I have consulted with over 110 biomedical research teams, with contributions including research hypothesis development/refinement, experimental design, careful selection of data modeling and hypothesis testing strategies, and summary of study results to inform future research studies and clinical practice in the greater scientific community.
I enjoy learning about algorithms, programming languages, and platforms that facilitate scientific computation. I value the opportunity to regularly attend scientific meetings in order to network with other data scientists and learn about new tools and algorithms that may be useful in my research. In addition, I have over 6 years of undergraduate/graduate-level mathematics and statistics teaching experience that have enhanced my ability to communicate technical ideas to non-statisticians.
I am looking to connect with an innovative, data-driven company that leverages modern technology and machine learning to gain insight from data.