Shiny Data Analyst

What you will do
In this role we are looking for individuals with a quantitative science background (statistics, data science, computer science, mathematics, or similar), database and programming expertise, and a passion for drug development. The candidate for this role will jointly collaborate with an analytic group within Global Statistical Science and the Biomedical Data Stewardship team. This role will have an opportunity to work across our client's pipeline to oversee the development of data visualization, statistical / machine learning algorithms, and analytic pipeline / package / applications in R/Shiny. Additionally, this role will work with study data and metadata to develop programming solutions to visualize data standards, compliance metrics, and to advance the application of a metadata repository. The role provides opportunities to develop leadership skills in clinical development strategy and to address scientific questions through practical quantitative thinking.
In this role you will:
Build machine learning and other statistical models, as well as support their implementation and deployment through a good understanding of the Software Development Life Cycle
Perform data analyses in a wide range of data and analytics solutions, from descriptive to predictive, using advanced statistical and machine learning models
Leverage large data sets to conduct end-to-end analytics that will include data gathering, requirements specifications, processing, analytics, ongoing deliverables, and presentations
Collaborate with cross-functional colleagues (e.g., clinical scientists, safety scientists, study statisticians, programmers), and work closely with subject matter experts to deliver value by developing Client, practical, scientific data-driven solutions to meet business needs and to develop data visualization, statistical modeling, machine learning/predictive modeling algorithm in R to address scientific questions in development
Design and develop R-based Markdown documents, interactive visualizations, and Shiny applications to facilitate centralized tool building and enable real-time, high-quality analysis delivery
Lead interactions with statistical programming and data standard teams to streamline ADaM data development for real-time statistical analysis
Support statistical analyses of individual studies/projects
Develop a knowledge of Client's statistical policies, strategies, and process improvement initiatives
Build a comprehensive understanding of Client's data standards structure across stages of development
Build a comprehensive understanding of the metadata repository (MDR) product and design, and identify areas for improvement and expansion
Develop integrations with the MDR enabling visualization of the standards, compliance reporting, and metrics
Use SAS Enterprise Guide to develop and maintain SAS programs to extract Data Element Standards and to create datasets, reports, and workbooks
Develop and maintain VBA programs to post-process SAS output and automate repetitive document/file processing activities
What we expect of you
Basic Qualifications:
Doctoral degree (statistics, data science, computer science, mathematics or similar) and 2 years of quantitative science experience OR
Master's degree and 6 years quantitative science experience OR
Bachelor's degree and 8 years quantitative science experience OR
Associate degree and 10 years quantitative science experience OR
High school diploma / GED and 12 years of quantitative science experience
Proficient in R programming language and Shiny app development
Proficient in SAS programming language
Good understanding of clinical trials and clinical data
Preferred Qualifications:
Doctoral degree or master's degree with relevant experience
4 or more years of pharmaceutical/biotech experience in drug development
Proven project leadership experience
Experience in designing, analyzing, and reporting clinical trials
Excellent R computing, modeling, and visualization skills
Experience working with multiple languages in the Shiny environment (for example. JavaScript, CSS, Python, VBA, etc.)
Independent and self-motivated
Strong organizational skills such that facilitate multi-tasking in time-sensitive environments
Strong communication and collaboration skills