The CCDL's data scientist is a point person on data-intensive cancer biology within the team. The data scientist performs analyses that help us design better software for the research community, performs analyses that seek to move towards cures for one or more childhood cancers, and works with the director to guide the biological challenges addressed by the lab and to enhance CCDL-led training efforts. The data scientist will envision solutions that serve a community of dedicated scientists and clinicians, including those who receive grants from ALSF. This team member will be expected to identify opportunities to enhance CCDL offerings. The data scientist will seek to make sure that analyses that are performed in the CCDL are robust and reliable. The data scientist may, at times, be asked to participate in drafting scientific manuscripts describing work from within the CCDL either as a primary author or as a collaborating author with other groups.
The CCDL position will provide the data scientist with the opportunity to envision and enhance data-processing systems as well as systems that enable the user-guided analysis and interpretation of large-scale datasets. This member of the team will need an understanding of how to perform robust analyses of biological data. Working in the CCDL also provides a unique opportunity to interact with the childhood cancer research community and its supporters at ALSF.
• Work with developers to design systems that address a pressing need in cancer biology.
• Perform and summarize analyses that seek to reveal new paths to treatment of childhood cancers or enhance CCDL offerings.
• . Write clean, maintainable source code.
• Expertise in the collection of activities now coming to be known as “biological data science.”
• Expertise with machine learning for large heterogeneous biological datasets.
• Expertise in or the ability to transition to R or Python. If R, a willingness to become conversant in Python.
• PhD in Genetics, Genomics, Computer Science, Bioinformatics, or related field.
Applications that include either a portfolio with work samples or demonstrable contributions to open source projects are preferred.
This full-time opportunity offers a competitive salary and benefits package. Interested candidates should submit a CV/resume with cover letter describing your interest and why you would be the right fit for this position to firstname.lastname@example.org.