DaSL Core Values
Read about DaSL’s Core Values and how we foster a supportive data science community at Fred Hutch and beyond.
DaSL is Hiring
Check out our jobs page for links to positions we have open and other Data Science jobs at the Fred Hutch.
DaSL Year 1 Strategic Priorities
Workforce Training & Expertise
DaSL champions the democratization of data science expertise through comprehensive training and educational resources. We have launched open access training resources for people with a variety of levels of expertise, reaching over 8 million people globally. Our training group will expand our offerings to include in-person, hybrid and self-paced courses, workshops, seminars and documentation catering to a range of working professionals and trainees as well as the general public.
Our Translational Analytics effort will support expanded access to the Fred Hutch patient clinical data via facilitated clinical data requests, new self-service and supportive tools to support data exploration and access, and the development of data processing, extraction and de-identification software and tools. We also collaborate with the Sloan Precision Oncology Institute and OTR to help coordinate and support their data and technology needs.
Policy and Governance
DaSL supports efforts across the Fred Hutch regarding data policy and governance including data use agreements, software licensing, data oriented tech-transfer issues and guidance regarding IRB oversight of data use. We also support efforts surrounding Fred Hutch-wide patient consent processes, community oriented cancer education efforts, and human data stewardship literacy in the clinical and research community.
Data Infrastructure and Strategy
Fred Hutch’s recent merger to form a hybrid clinical care and research institute brings a diversity of focus, skills, interests and capabilities that can spur innovation. To foster a feedback loop between biomedical discovery and clinical care, DaSL aims to create a robust and coordinated data ecosystem at Fred Hutch via guiding data infrastructure development with a comprehensive data strategy. This includes data policy & governance, technology & infrastructure, tools & training with a focus on democratization of comprehensive, timely and secure data access.
Data Product & Technology Development
We aim to support both research and clinical staff by developing data products, including web applications, data analysis tools, process automation, and scientific software, to enable effective data use and integration into research and clinical care. Our collaborative approach not only supports researchers in piloting, sharing and publishing custom applications and software via our RDI group, but also involves partnering with the Business Development office to support potential commercialization or licensing and to integrate these tools into the Fred Hutch data ecosystem.
Tech & Philanthropic Partnerships
We will support technology and philanthropic partnerships by identifying emerging ideas and projects within Fred Hutch that, in collaboration with the broader data and technology industry, will advance our understanding of disease, therapeutics, and patient outcomes. Building on existing partnerships with companies like AWS and Microsoft, we aim to broaden the scope and impact of these collaborations to find new opportunities that align with Fred Hutch’s ongoing research and clinical needs.
DaSL is committed to fostering a vibrant community centered around data science at Fred Hutch to encourage democratized access to data science expertise, collaborations and mentorship. WE recognize the value of community connections across diverse research and clinical arenas, and strive to connect individuals to community through the efforts such as the Fred Hutch Data Slack workspace, our Monday Morning Data Science newsletter, as well as hosting periodic events to bring people together in the DaSL Lounge.
Documentation & Knowledge Sharing
A critical part of supporting an ever evolving and advancing data community filled with people interacting with data in different ways and scales is an overall focus on open documentation to facilitate knowledge sharing. We lead and collaborate on the Biomedical Data Science Wiki, which aims to share best practices and foster community consensus and serves as an open, community knowledgebase, and valuable source to learn about available data science resources at the Fred Hutch and beyond.