Data Scientist (May 2021-) - Member of the Leidos Data Science Team supporting the National Center for Immunization and Respiratory Diseases at the CDCStatistician (Sept 2020-May 2021)- Lead analytic surveillance efforts for COVID-19 response within US Dialysis facilities and hospital acquired infections at the Centers of Disease Control and Prevention's (CDC) National Healthcare Safety Network (NHSN) within the National Center for Emerging and Zoonotic Infectious Diseases.

- Provide statistical oversight of clinical trials and longitudinal studies assuring adequate quality and consistency with project requirements.- Support and lead efforts in applying data science tools in imaging, omics and etc.- Responsible for protocol development including study design, sample size estimation, randomization, and statistical analysis plan for brain, stress, hypertension and ageing studies.- Responsible for assuring that data for statistical analyses are complete… Show more - Provide statistical oversight of clinical trials and longitudinal studies assuring adequate quality and consistency with project requirements.- Support and lead efforts in applying data science tools in imaging, omics and etc.- Responsible for protocol development including study design, sample size estimation, randomization, and statistical analysis plan for brain, stress, hypertension and ageing studies.- Responsible for assuring that data for statistical analyses are complete, accurate and consistent.- Responsible for accuracy and completeness of database quality checks. Show less

- Responsible for supporting various teams within the Division of Viral Diseases with statistical analyses, data management and reporting.- Lead surveillance efforts to enhance and improve the quality of data and systems.- Projects range from working with the New Vaccine Surveillance Network (NVSN) of various Children’s Hospitals in the research areas of acute respiratory infections (ARI), influenza and acute gastroenteritis to the National Health and Nutrition Examination Survey… Show more - Responsible for supporting various teams within the Division of Viral Diseases with statistical analyses, data management and reporting.- Lead surveillance efforts to enhance and improve the quality of data and systems.- Projects range from working with the New Vaccine Surveillance Network (NVSN) of various Children’s Hospitals in the research areas of acute respiratory infections (ARI), influenza and acute gastroenteritis to the National Health and Nutrition Examination Survey (NHANES)-HPV team. Show less

- Introduction to R programming instructor for the School of Public.- Statistical methods lab instructor for Global Health and Health Policy and Management graduate students.- Applied Linear Models lab instructor for Epidemiology master and doctoral students.

- Statistician on various NIH studies in MDR/XDR Tuberculosis and drug-resistant HIV in Kwa Zula-Natal, South Africa.- Responsible for data management, reporting and statistical analyses. - Work contributed to multiple publications in NEJM and various AIDS research journals.

- Assist core with data migration, normalization, survey optimization, data modeling, interoperability, analytics, continuity of care analyses.

-Support biomedical investigators in cleaning, blending and analyzing multiple national sources of biospecimen and tuberculosis databases using R and SAS. -Collaboration with the CDC and South Africa NICD.

- Collaborate with principal investigators, medical professionals and biostatisticians to support their needs for statistical programming, data cleaning and management. - SAS programmer.-Create SAS code to generate cleaned integrated complex Medicare analytic datasets. - Perform data management and analysis using STATA and SPSS.- Document SAS programs, create and maintain organized project directories according to strict standard operating procedures.

- Goal was to model and test a fairly new nonlinear mathematical model used on adults that had not yet been used on infants to assess the autonomic nervous system. - Our study focus was to assess the autonomic nervous system of infants diagnosed with Hypo-plastic left heart syndrome compared to normal infants.- This project was part of a long term goal to determine what may be causing infant mortality of 20-30% after the first surgery completed to correct the syndrome.-Models… Show more - Goal was to model and test a fairly new nonlinear mathematical model used on adults that had not yet been used on infants to assess the autonomic nervous system. - Our study focus was to assess the autonomic nervous system of infants diagnosed with Hypo-plastic left heart syndrome compared to normal infants.- This project was part of a long term goal to determine what may be causing infant mortality of 20-30% after the first surgery completed to correct the syndrome.-Models created and studied in Matlab Show less

- Statistical Research on Leukemia mortality rates around 104 U.S nuclear plants. - Focus was spatial analysis on death rates using three global clustering models: Moran’s I, Tango’s Index, Oden’s I pop. - These models allowed us to compare their respective test statistics and inferences.- Programming and analysis in statistical software R.- Publication title “A Geographical and Statistical Analysis of Childhood Leukemia Deaths Relating To The Locations of Nuclear Power Plants”… Show more - Statistical Research on Leukemia mortality rates around 104 U.S nuclear plants. - Focus was spatial analysis on death rates using three global clustering models: Moran’s I, Tango’s Index, Oden’s I pop. - These models allowed us to compare their respective test statistics and inferences.- Programming and analysis in statistical software R.- Publication title “A Geographical and Statistical Analysis of Childhood Leukemia Deaths Relating To The Locations of Nuclear Power Plants” in the Advances and Applications in Statistical Sciences Journal. Show less

- Biostatistics and R programming training and research- Beta testing of an R package called MAGMA designed to analyze large data sets like those in spatial statistics using both the CPU and GPU to make computing time faster.

- Applied statistics training and research.- Analyses performed using SAS.