Statistical Programmer II

Job Title

Responsibilities:

Team provides customized real-world data and real-world evidence solutions to address the most important research questions across clinical development, market access, and commercial use cases for our life sciences partners.

Independently translate analytic specifications from a statistical analysis plan into R code to create analytic datasets, generating descriptive and inferential statistics, data visualizations, often involving Client variables or complex statistical methods, in consultation with the study principal investigator.

Serve as subject matter expert on appropriate use cases for, and nuances of, the variety of different Flatiron data modalities, including EHR-derived real-world data, clinico-genomics data, ML-extracted data, and claims data.

Develop a proficient understanding of cancer biology, therapy, and/or epidemiology across multiple major tumor types and appropriately apply this understanding when crafting analytic code.

Provide mentorship and support to more junior statistical programming staff.

Collaborate with cross-functional stakeholders across our medical and scientific organization to execute and deliver on client-sponsored research studies in an accurate, effective, and timely manner.

Contribute to continuous improvement of Flatiron's proprietary analytical tooling and templates, at times acting as liaison to the relevant teams and stakeholders.

Continue to develop a deeper understanding of real-world data and related methodologies used to generate real-world evidence.

Work closely with Epidemiology and Biostatistics to assure output quality by providing expert feedback on SAP, Analytic/TLF specifications from functional perspectivly.

Requirements:

Doctorate degree (e.g., PhD, ScD, DrPH) in Biostatistics/Statistics, Data Science, Bioinformatics, Biological Sciences, Public Health, Math, or a closely related field with 3-4 years of relevant experience, or a Master's degree with 6-7 years of relevant experience or a Bachelor's degree with 7-8 years of relevant experience.

In addition, you're an analytical thinker and excellent communicator with experience analyzing real-world data (e.g., healthcare claims or electronic health records).

Excellent programmer in R (including tidyverse) and are proficient working in Git-based environments (e.g., Github, Gitlab).

Solid experience in creating Tables, Listings, and Graphs using R packages.

Create/review programming documents (e.g., programming plan, specification for datasets and output template).

Knowledge of ICH guidelines, FDA / EMA / other regulatory authority guidance from a programming standpoint.

Extensive experience with large healthcare-related datasets (e.g., administrative claims, electronic medical records, genomics).

Experience leading teams, either as a manager or project/team lead.

Familiar with CDISC conventions, i.e. SDTM and ADaM models (using SAS) and related controlled terminologies, and knowledge or some experience using these models.