● Oversee Jr. biostatisticians with articulating key questions, defining study designs, and implementing statistical methodologies● Strong proficiency in querying and manipulating large data sets and apply appropriate statistical methodologies● Lead projects and drive meetings to interpret or visualize insights or findings in a concise narrative to a broad range of team members● Build effective collaborations within a highly cross-functional ecosystem to drive projects growth

● 8+years of hands-on experience doing quantitative analysis and data visualization using SQL, Python, SAS and Stata● Built strong fundamentals in statistics and ML methods such as A/B Testing, sampling data, regression, causal-inferential, clustering, classification, decision trees, random forest, time series, prediction model, survival analysis, cross-validation, and bootstrapping● Proficiency in creating, automating, and maintain reporting that drives an improved understanding of projects● Proactively socialize insights and translated complicated findings or technical approaches into easy-to-understand data stories.

● Consolidated internal and external collaborator data sources into a centralized database through data preprocessing and standardization of data formats● Developed standardization templates of data files for future analysis through database development, data collection, and data cleaning

● Coordinate all data management, including data mining, maintaining databases, and merging different sources data into a unified view for statistical analyses● Led end-to-end analytical projects including designing analytical plans, developing project-specific SAS programs, running quantitative and qualitative analyses, conducting modeling from formulation optimization, visualizing and summarizing results● Collaboratively created and managed projects from timeline creation to project completion, including literature review, developing research hypotheses and presentation of results to senior management● Compiled and delivered documentation such as scientific manuscripts for methodology and results sections to support publication activities and scientific presentations

• Contributed to data mining from billions of medical records and reformatted as uniform dataset for analysis use;• Experienced in cleaning, recoding, and merging multi-sources clinical datasets (Big Data). • Participated as the key statistical programmer in a study of identifying the incidence and risk factors of prostate cancers in one of anti-diabetic drugs users v.s. non-users.• Performed Survival Analysis (Cox Regression) for large population-based studies.• Prepared tables and graphs for the reports and publication paper and presented results.

·Analyzed proficiency in data analysis using multivariate logistical/regression, multilevel methods.·Evaluated and conduct procedures for data management, monitor survey data quality.·Formatting and merging several years dataset and created a comprehensive codebook and databook.·Promoted experience on independently performing multiple datasets in pre/inter-conceptional health, prenatal care, maternal medical conditions during pregnancy, psychosocial risk factors, and behavioral risk factors area.·Performed abstracts (APHA accepted) and presented posters on several annually Science Summits.·Taught basics of SAS programming skills to new users.

·Strengthened experience in survey review, telephone interview, data cleaning and management.·Developed “Prenatal Care & Low Birth Weight” research and academic publication independently. ·Designed chart/tables, Healthy Brief fact sheets & reports for interpretation purposes.·Presented to the audiences with clinical training, senior epidemiologists and key stakeholders.