Elizabeth L. Email and Phone Number

A role that involves managing projects within Takeda with data mining, data management, statistical analyses, Shiny application development, and AI model creation and maintenance. Directly responsible for creating and maintaining eight statistical applications that implement general linear modeling, cohort balancing, DAG creation, indirect treatment comparisons, and time-series modeling. Also, responsible for managing two projects involving ETL processing and machine learning model implementation (NLP and RNN) of real-world adverse event data for business needs.Knowledgeable in statistical analyses, statistic application development in R Shiny, and creating big data deep learning models (in R and Python) with respect to adverse event data, clinical trial data, and real world evidence (RWE) data in post-marketing studies.

A role that includes data mining, data management, statistical analyses, Shiny application development, and AI model creation and management for Takeda as a Senior Data Scientist.Responsibilities include creating statistic applications in R Shiny and deep learning models using PyTorch and Python with respect to adverse events.

Created statistical analysis protocols and designs with client collaboration based on large registry data.Implemented numerous analytical techniques including but not limited to: Linear, Logistic, Ordinal, Poisson, Negative Binomial, Zero-Inflated, Survival Analyses, Kaplan Meier, Restricted Mean Survival Time, Cox-Proportional Hazard Modeling, Propensity Scoring and WeightingCreated and managed a custom R package designed to format and standardize publishable tables, reports, and graphs and create custom summary statisticsWrote and peer-edited executive summaries, manuscripts, and abstracts as well as presented the results to a variety of audiences.

Implemented numerous analytical techniques, including but not limited to: Linear, Logistic, Ordinal, Poisson, Negative Binomial, Zero-Inflated, Survival Analyses, Kaplan Meier, Restricted Mean Survival Time, Cox-Proportional Hazard Modeling, Propensity Scoring and WeightingCreated and managed a custom R package designed to format and standardize publishable tables, reports, and graphs and create custom summary statistics.

Responsible for designing, analyzing, interpreting and publishing clinical trial, prospective and retrospective study data. Depending on the primary objectives, methodologies implemented include, but not limited to, descriptive summaries, generalized regression modeling (linear, logistic, ordinal, poisson, negative binomial, and multilevel/mixed), agreement (ICC, Cohen's weighted and unweighted kappa), K-means and hierarchal clustering, gradient boosted models (gbm, xgboost), random forest, neural networks, and convolutional neural networks. Primarily work in R (in Rstudio), SAS and Python.Familiar with DSMB and FDA reporting as well as maintaining and analyzing data on clinical trials with specific requirements, deadlines, and protocols. Currently working on the Mayo Clinic Convalescent Plasma Expanded Access Program.

Worked in Python to model probability distributions, process workflows and models. Implemented data quality checks through goodness of fit and tests of differences while exploring relationships between extracted features and outcomes of interest. Participated in extensive feature extraction with text using TFIDF, Word2Vec, and grouping similar features with K-means clustering using cosine similarity, euclidean distance, and Jaccard distance. Also responsible for extracting, transforming, and validating big datasets using Spark with AWS.

Responsible for creating SAS applications and visualize client data and performance. Additionally responsible for structuring the data ETL process.

Responsible for researching, modeling, and analyzing data using statistical methods to enhance client performance on the Strategy and Analytics Team. Additionally responsible for creating, pulling, and managing reports to assist and make recommendations to clients in SQL.

Responsible for managing data while creating, pulling, and analyzing reports to assist and make recommendations to clients in SQL. Assist in researching and enhancing client performance through company programs and statistical analysis.

Created the DME’s automated test script for testing major client facing applications using Selenium, C#, and .net in Microsoft Visual Studios. Worked jointly with the team to push major projects and manually test client facing applications.

Assist in reviewing manual test scripts and creating an automation strategy for automating test scripts.