Yubing Wan Email & Phone Number

Frederick, Md

• Led statistical analysis for multiple FDA-approved clinical trials, developing and executing statistical analysis plans (SAPs), and delivering insightful reports to stakeholders, driving project success. • Advanced and implemented an ensemble approach combining machine learning and deep learning algorithms for scalable and interpretable omics analytics, offering an innovative solution for big genomic data challenges. • Leveraged expertise in data wrangling and architecture to contribute to the development of a cloud-based data platform, now available as a Software as a Service (SaaS) product for clients in the pharmaceutical and biotechnology sectors. • Supervised a team of two Data Scientists (levels II and III), overseeing daily tasks, ensuring project milestones were met and facilitating cross-functional collaboration. • Led flagship projects for premium clients using Atlassian and Slack tools. • Developed R Shiny applications serving as data analytics platforms, facilitating analysis pipelines of clinical and biomarker data for clinical trial operations and real-time delivery of results and visualizations. • Integrated DevOps practices, including Airflow and CI/CD, to enhance automation of workflow and data extraction, transformation, and loading (ETL) processes. • Monitored data quality control, cleaning, and analysis, steering the transformation of initial data sources into SDTM and ADaM analysis ready datasets, ensuring integrity and alignment with study design objectives. • Shared expertise in statistical methodology, data science, and clinical trial through regular presentations in meetings and seminars. • Enhanced codebase modularity and validity by championing functional programming, achieving reduction in code redundancy and promoting sustainable agile software development within the team.

Frederick, Md

• Conducted genome-wide association and network analysis on a Phase IV drug study dataset, uncovered a 20-SNP genomic signature to stratify patient groups, facilitating the creation of a complementary diagnostic tool. • Crafted and implemented Bayesian hierarchical models across various clinical trial studies with a focus on exploratory objectives, enhancing patient stratification precision and optimizing drug efficacy outcomes. • Interacted with clients from pharmaceutical and biotech companies, research organizations, ensuring clear communication and collaboration. • Led the development and implementation of tables, listings, and figures (TLF) with the analytics team. • Crafted statistical methodologies for SAPs and reviewed clinical study reports (CSRs) for diverse FDA-approved trials, supporting pharmaceutical and biotech clients. • Innovated reusable SAS macros, Python and R packages for advanced data manipulation and pipelines, boosting team workflow efficiency and enhancing consistency and quality in data analysis and operations. • Developed and applied data processing and analytical pipelines, adhering to SAP, SOP, GCP, and HIPAA guidelines throughout delivery and submission processes.

Farmington, Ct 06030

• Designed a machine learning methodology to predict chromatin structures in an aging study, proved viability of an in silico generic screening method, secured funding renewal for the research. • Developed dimensionality reduction algorithms to optimize high-dimensional NGS data analysis, facilitating cross-disciplinary collaborations that generated new funding and publication prospects.

Louisville, Ky

• Developed a multiple imputation based weighted elastic net method for variable selection and prediction with missing data, and applied this method to examine the correlated predictors for the endothelial function in an ex-vivo experiment.• Designed a new method utilizing penalized I-splines to construct monotonic single-index models for capturing different patterns of drug interaction and dose response.

Edinburg, Tx

Edinburg, Tx

Doctor Of Philosophy (Ph.D.), Biostatistics

Master Of Science (M.S.), Mathematics

Bachelor Of Science (B.S.), Mathematics