The Department of Data Science at the Dana Farber Cancer Institute (DFCI) seeks to collaborate with basic biologists and clinical researchers to better understand cancer and improve treatment by developing new statistical methods and data analysis pipelines.
Requirements
- Substantial experience in two or more of: scientific computing; data technologies; user interfaces; containerization; or distributed computing
- Experience in package development and advanced computing in the R ecosystem
- Natural language processing experience preferred
- Shiny, Spyre, Flask, WebDev and prototyping experience preferred
- JupyterHub, Sun Grid Engine, Google Cloud Platform, AWS experience preferred
- Experienced in data science methodologies and techniques, e.g. hypothesis testing, classification, regression, clustering, feature allocation, deep learning, time-series analysis, network modeling, feature selection/engineering
Responsibilities
- Meet and consult with scientists requiring data science support and design plans and solutions
- Delivery of results for projects
- Work as part of the broader team to identify longer-term solutions that will improve quality, speed and efficacy of our current projects and programs
- Evaluate and benchmark new libraries; prototype and pipeline development
- Deep data science skills, at the interface between computer science and statistics
- Design plans and solutions for data science support
- Work on projects to improve quality, speed and efficacy
Other
- Excellent communication and effective problem-solving skills, track record in serving a variety of diverse customers and projects
- Ability to work independently, prioritize, and manage people if needed, within an environment with ever changing priorities
- PhD or equivalent experience with evidence of impact in data science applied to real life problems in a research setting ideally within a clinical research environment
- 5 to 8 years of experience post PhD
- Prior experience supervising at least 1 person preferred
