Data Scientist - Radiology AI

We are seeking an intelligent, hard-working, and dynamic individual to serve as the Radiology AI area leader and senior data scientist within the Artificial Intelligence Operations and Data Science Services group (AIOS) in the Informatics & Analytics department of Dana-Farber Cancer Institute – a teaching affiliate of Harvard Medical School. The team works on both short-term priorities identified by our top clinicians, as well as on long-term institutional efforts that aim at revolutionizing the way the Institute conducts basic cancer research and provides best-in-class clinical oncology to our patients.

AIOS is part of the department serving some of the most prominent research and clinical programs at the Institute, from basic to translational research, to clinical deployment, and operationalization. The AIOS group encompasses expertise in AI, data science, machine learning, computer vision, NLP, production deployment, cloud infrastructure, data engineering, project management standards, and data labeling. Dana-Farber Cancer Institute (DFCI) provides expert, compassionate, and equitable care to children, adults, and their families, while advancing the understanding, diagnosis, treatment, cure, and prevention of cancer and related diseases. DFCI trains new generations of clinicians and scientists, disseminate innovative patient therapies and scientific discoveries around the world, and reduce the impact of cancer, while maintaining a focus on those communities who have been historically marginalized.

This Position is fully remote with flexibility to come onsite if desired.

Located in Boston and the surrounding communities, Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.

Responsibilities

• Lead the Radiology AI Functional Area

• Develop, execute, and yearly revise the strategy for the Functional Area – inclusive of creation of new data assets, new code assets, and new services to add to the Radiology AI offering
• Implement multiple Radiology AI projects in partnership with our clients, and joint dissemination at DFCI and outside
• Work closely with the Associate Director of AI Operations and Data Science Svcs providing area expertise for Radiology AI and aligning the group strategy with the Functional Area strategy
• Demonstrate excellent soft skills, such as excellent oral, written, and presentation/communication skills

• Deliver Scientific Excellence

• Sustain Dana-Farber's leadership in Radiology AI science by deploying state-of-the-art research methods, incorporating emerging best-in-class techniques as they enter the literature, and contributing to the design and conduct of research that advances the state of the art
• Delivery of results for projects on time and on budget
• Maintain a landscape of the intellectual property developed within the Functional Area
• Contribute to patents, scientific manuscripts, and presentations as required

• Effectively Support our Client Base

• Managing internal and external clients and leading and executing projects end-to-end
• Demonstrate excellent communication and effective problem-solving skills informed by experience in serving a variety of diverse customers and projects
• Help the team maintain a net-promoter score >= 8 across all current Clients, as assessed by end-of-year ratings
• Attract new research clients to the chargeback program
• Meet and consult with scientists requiring Radiology AI support to designing plans and solutions

• Manage a Diverse Team

• Ability to work independently, prioritize, and manage people if needed, within an environment with ever changing priorities
• Scope and delegate work to others, as well as support them during their projects
• Mentor and supervise team personnel in a collegial yet accountable manner by fostering ownership of projects and deliverables

• Support the AI Operations and Data Science Team

• Actively and flexibly support the Institute's mission across teams and administrative groups
• Coordinate with vendors and external consulting firms; evaluate their work; scope new interactions; evaluate their plans; compare vendor offerings when needed
• Actively contribute to the growth of the AI Operations and Data Science Services group, in terms of scope, access, responsibilities, and new projects that are trusted with the group

• MS in computer science / computer engineering / electrical engineering or another highly computational field required. Ph.D. and postdoctoral experience preferred.
• Detailed knowledge of SOTA computer vision architectures, including CNNs (convolutional neural networks) and transformers

• Ability to quickly read and digest substantial amounts of information from the newest publications in this area
• The ideal candidate should be able to take this information and make informed decisions about suitability for use cases and assess if a direction of research is promising
• Exposure to transfer learning/self-supervised learning highly preferred

• Extensive prior work/publications working with at least one of the following image modalities (CT, MRI, x-ray) is a must have

• Candidate should be familiar with the common python libraries used to parse these modalities, including SimpleITK, PyNRRD, PyDICOM

• Prior work with semantic segmentation, particularly for highly imbalanced datasets
• Deep understanding of modern deep learning libraries such as PyTorch or Tensorflow
• Experience with most of the following libraries: matplotlib, numpy, OpenCV, pandas
• Understanding of basic software engineering principles, including the software-development lifecycle, git, linux, and unit testing
• Understanding of at least one of the primary cloud computing environments (Azure, GCP, AWZ)
• Experience leading and growing a small team and appropriately allocating work
• Ability to oversee multiple client projects from both a high-level and low-level perspective
• Ability to manage client expectations

• Identify at-risk critical pathways early in the development process and work with clients and AIOS project managers to produce sustainable work plans.
• Professionally discuss client expectations to sustain client satisfaction

• Ability to track progress of multiple projects using standard organizational software including SmartSheets and LucidChart

• Ensure that deadlines and relative prioritization among projects are communicated to the AIOS group project managers and clients
• Coordinate task prioritization with clients, AIOS project managers, and team members to ensure on-time completion of key deliverables

• Experience with Project Management Interface

• Demonstrated ability to work with AIOS project managers in all aspect of project and client management. This will include scoping, planning, executing, and communicating project deliverables effectively with AIOS clients.

• Record of accomplishment of successfully conducting research that has led to peer-reviewed publications in an academic or corporate environment is preferred

Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other groups as protected by law. 

At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong. As relentless as we are in our mission to reduce the burden of cancer for all, we are equally committed to diversifying our faculty and staff. Cancer knows no boundaries and when it comes to hiring the most dedicated and diverse professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.