Job Description

Overview Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington. With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world’s leading cancer, infectious disease and biomedical research centers. Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover new cures to the world’s deadliest diseases and make life beyond cancer a reality. At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems. The laboratory of Dr. Nasa Sinnott-Armstrong ( ) has a part-time Data Scientist II position open in the Computational Biology Program of the Public Health Sciences Division. At the Sinnott-Armstrong Lab, we are interested in common human diseases and patient experience to pursue transformative advancements in healthcare. We are dedicated to understanding the map between genotype, environment, and phenotype at a population level. We aim to use the diagnosis and management of Lyme disease, chronic illnesses, and Valley fever as models to understand the public health landscape as we move forward. We focus on critical areas of public health (ie. environmental health, biostatistics, epidemiology) and prioritize collaborative research projects across institutions, to redefine biomedical research into a multifaceted practice. We use Genome-Wide Association Studies (GWAS), database analysis of patient records in combination with biochemical and molecular approaches to understand the immune response and mechanisms of the Lyme disease-causing Borrelia burgdorferi. Our research aims to improve health outcomes and access by prioritizing patient experiences and fostering innovative, inclusive practices. We are committed to advancing healthcare through collaboration, integrity, and a dedication to personal and professional growth. By reimagining conventional scientific practices, we strive to make meaningful impacts on public health and precision medicine. Our core values include a patient-centered approach, collaboration and innovation, personal and professional growth, and a commitment to diversity, equity, and inclusion. At our lab, we believe that research should be both impactful and enjoyable, and we are committed to creating a space where groundbreaking science meets a supportive and dynamic community. Together, we aim to redefine laboratory science and contribute to a more equitable and effective healthcare system. We work in an interdisciplinary team environment with many local and external experts. Key projects available for this position include participating in exciting collaborations around ELSI and bibliometrics of genetics and genomics; the genetics of ME/CFS and Fibromyalgia; the overlap of genetics and social determinants of health; and epidemiology and post-GWAS follow-up analysis of Lyme disease as well as of a number of early projects in lab, including time-varying GWAS, biomarker analyses, and the genetics of TB. There will be significant opportunity to engage in independent research projects as part of this position, and ability to act independently is a key component of the job. Candidates with strong interest and/or expertise in any of these research areas are highly encouraged to apply:

• Environmental health and health disparities research
• Gene-environment interactions
• Overlap of cardiometabolic and infectious diseases
• Community-based participatory research

This is a part time role, approximately 8hr/week initially. There is potential to increase up to full time depending on sponsor funding. Responsibilities Identify and integrate disparate data sources, both internal and external, including raw data from medical researchers, unstructured data from clinical experts, and well-established, publicly-available databases

• Develop and deploy machine learning algorithms, predictive models, and classification methods to advance cancer research and inform clinical decision making
• Deliver novel, data-driven insights to improve outcomes in the treatment of cancer
• Identify areas of growth for the data science initiative and actively engage in enhancing the breadth and reach of data science across Fred Hutch
• Collaborate with researchers and clinicians to identify high-impact opportunities for data science applications
• Manage data science projects from creation to completion
• Communicate results to technical and non-technical audiences

Qualifications

MINIMUM QUALIFICATIONS:

• A Bachelor’s degree or higher in computer science, data science, statistics, informatics, or equivalent.
• Core competency in at least one of the following: genetics and genomics, natural language processing, image processing, medical records or claims.
• Experience in software development in the context of machine learning, such as R, Python, or others
• A sound understanding of software development best practices (e.g., version control, unit testing, regression testing)
• A fundamental understanding of machine learning, both supervised and unsupervised, and experience with machine learning tools and applications
• A strong background in both formal statistics and predictive analytics, and some experience with the analytic process
• Software development in the context of machine learning, ideally in R or Python
• Strong written and oral communication skills, including report-writing, and presentation/visualization of analysis results

Preferred Qualifications

• Advanced degree (M.S. or Ph.D.) i n other areas of science with at least 2yrs of experience related to biostatistics.
• Interested in research on health disparities and social determinants of health
• Experience with analysis of metagenomics and/or microbiome sequencing datasets
• Mentorship experience – this role will be expected to supervise 1 to 2 postbaccalaureate scholars

To Apply, Please Submit Your Application With The Following

• Cover letter with a statement of research accomplishments and interests
• Curriculum vitae
• Names and email addresses of three references
• Two representative publications or preprints (if available)

The hourly pay range for this position is from $49.24 to $77.82 and pay offered will be based on experience and qualifications. Fred Hutchinson Cancer Center offers employees access to a retirement savings plan, an employee assistance program, paid sick leave (1 hour for every 30 hours worked), and prorated paid holidays (up to 13 days per year). Additional Information We are proud to be an Equal Employment Opportunity (EEO) and Vietnam Era Veterans Readjustment Assistance Act (VEVRAA) Employer. We do not discriminate on the basis of race, color, religion, creed, ancestry, national origin, sex, age, disability (physical or mental), marital or veteran status, genetic information, sexual orientation, gender identity, political ideology, or membership in any other legally protected class. We desire priority referrals of protected veterans. If due to a disability you need assistance/and or a reasonable accommodation during the application or recruiting process, please send a request to Human Resources at hrops@fredhutch.org or by calling 206-667-4700.

Job Tags

Hourly pay, Full time, Local area,

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