Data Scientist I, PCCTC

Memorial Sloan Kettering Cancer Center•New York, NY

11h•$113,100 - $180,900•Remote

About The Position

The Prostate Cancer Clinical Trials Consortium (PCCTC), incubated within Memorial Sloan Kettering (MSK), is seeking a Data Scientist I to join a collaborative team of clinical investigators and PCCTC staff working together on a single mission: to design, implement, and complete clinical trials and observational studies in prostate cancer, translating scientific discoveries to improve standards of care. We support this work through biostatistics and data science, data management, reporting, site management, and clinical operations across the clinical study lifecycle. You will develop and support data workflows, reproducible reporting, and R programming solutions for clinical trial and study needs. You will work with our Data Science Team and collaborate across Clinical Operations and Data Management to deliver clear, reliable data outputs.

Requirements

An undergraduate degree, preferably in statistics, data science, computer science, or a related field.
A strong working knowledge of R for data wrangling, analysis, and visualization, and preferably have experience using packages from the Tidyverse ecosystem.
Exposure to version control (git/GitHub).
Knowledge of R Markdown or Quarto.
Passion for data and creating new solutions to empower cancer care and clinical research.
Strong collaboration skills with the ability to partner effectively across cross-functional teams
Excellent communication skills, with the ability to translate complex data into clear, actionable insights
Strong problem-solving and critical thinking abilities in a data-driven environment
High attention to detail with a commitment to accuracy and data quality
Adaptable and proactive, with a growth mindset and interest in continuous learning

Nice To Haves

CDISC, SDTM, and ADaM regulatory requirements & clinical trial design
complex & relational data sets
building Shiny applications + R packages

Responsibilities

Maintain data pipelines for automated data processing suitable for downstream reporting, tabling, and summarizing
Execute and build upon reproducible reports via efficient code for complex tabling and data visualization.
Contribute to internal or external R packages.
Collaborate with Clinical Operations and Data Management teams to understand emerging trial and business needs, assess available data, and determine how to appropriately summarize and present results.