Data Scientist

The Alex’s Lemonade Stand Foundation partners with the Childhood Cancer Data Lab to advance data-intensive work in pediatric cancer biology. In this Data Scientist role, you will act as a point person within the Data Lab, helping shape biological problem-solving while improving data-processing and user-guided analysis systems for large-scale multi-omic datasets.

You will collaborate on analyses that clarify pathways toward better treatments and strengthen Data Lab offerings, spanning multiple data modalities and contributing maintainable code, documentation, and instructional materials. The role also includes representing the Foundation and the Data Lab at national conferences.

Key Responsibilities

• Collaborate with the Data Lab Data Science Manager to guide the biological challenges addressed by the Lab and/or strengthen Data Lab training efforts
• Perform and summarize analyses aimed at uncovering new paths to treatment for childhood cancers, and enhance Data Lab offerings in partnership with internal teams and external collaborators
• Integrate and harmonize multiple data modalities (including transcriptomic, genomic, epigenomic, proteomic, and imaging data) to answer questions in pediatric cancer biology
• Work with Engineering and Design teams to design systems addressing pressing needs in cancer biology
• Write and review clean, maintainable source code, documentation, and instructional material intended for public consumption
• Represent ALSF and the Data Lab at national conferences
• Support additional duties and special projects as assigned by Foundation needs

Required Qualifications

• Education: PhD in Genetics, Genomics, Computer Science, Bioinformatics, or a related field
• Data analysis expertise: rigorous analysis of high-dimensional biological data (biological data science)
• Programming: expertise in, or ability to transition to, R or Python
• Communication: excellent written communication skills
• Work authorization: must be authorized to work in the U.S.; no visa sponsorship is available for this role

Preferred Qualifications

• Demonstrable contributions to codebases for scientific projects
• Evidence of collaborative scientific research through peer-reviewed publications or preprints
• Track record in cancer research
• Experience with workflow management systems such as Nextflow
• Cloud computing experience, such as Amazon Web Services (AWS)
• Experience developing or adapting instructional material
• Experience writing and reviewing analytical code in a collaborative environment
• Broad experience across multiple data modalities; single-cell and/or bulk transcriptomics and integration of additional omics data types are a plus
• Interest or experience applying machine learning and statistical methods to biological data

Tools and Technologies

• R
• Python
• Nextflow
• Amazon Web Services (AWS)

Work Location and Schedule

• Remote role
• Candidates must be available to work core hours aligned with Eastern Standard Time (EST)
• Candidates located within the greater Philadelphia metropolitan area are preferred

Compensation: USD 90,000 to 121,000 per year.