Date Written: October 7, 2026
Location: Remote, Full-time
Department: Scientific/Research/Clinical
Reports to: Director Preclinical Initiatives
Wage Category: Exempt

The Children’s Tumor Foundation (CTF) is not a traditional research foundation. We operate as a patient-centered drug discovery engine for NF, a group of genetic conditions that cause tumors to grow on nerves affecting 1 in 2,000 individuals. We operate by accelerating the full continuum of scientific discovery, from basic research through translation to clinical trials and approved treatments — while empowering patients and building the financial infrastructure to support that journey. We catalyze progress by uniting academia, industry, regulators, and patient advocates around shared goals.

General Summary

The Biomedical Data Scientist will drive CTF’s efforts to turn neurofibromatosis (NF) data into actionable insights for drug discovery, positioning the Foundation as a leader in NF data. Working closely with CTF’s Science teams, this role integrates research, clinical and publicly available data to identify and prioritize therapeutic opportunities across NF1, NF2-related schwannomatosis, and non NF2-related schwannomatosis. The Biomedical Data Scientist will also work closely with vendors to steward CTF’s NF data ecosystem, lead CTF’s AI-enabled research resource for the NF community, and share data and findings with the broader research community. The ideal candidate is a self-starter with strong technical skills in bioinformatics, data integration, analysis, and visualization, strong writing skills, and a passion for advancing NF research.

Principal Duties and Responsibilities

• NF Data Ecosystem Stewardship: Serve as CTF’s subject matter expert for the NF Data Portal and associated analysis platforms. Work with data vendors and external data partners to track data sharing plans and milestones, identify new data sources, and ensure the quality, integrity, accessibility, and reuse of NF datasets. Manage subscriptions to various platforms.

• Data-Driven Target Discovery: Lead integrated analyses of genomic, molecular, clinical, imaging, and publicly available datasets to identify, prioritize, and validate therapeutic targets for NF. Work closely with CTF’s Drug Scout and Preclinical Initiatives teams and with NF researchers to translate findings into therapeutic hypotheses, target recommendations, and opportunities for preclinical validation. Create clear visualizations and summaries that inform CTF’s research recommendations.

• AI-Enabled Research: Evaluate and apply emerging AI and computational approaches to accelerate NF data integration and hypothesis generation. Serve as administrator of CTF’s Anthropic (Claude) workspace for the NF community, leading its build-out by surfacing NF datasets, publications, and sample analyses, managing access, and gathering user feedback.

• Community Engagement and Dissemination: Represent CTF and collaborate with Key Opinion Leaders to author peer-reviewed publications and present findings at conferences. Implement and manage data science workshops and platform sessions at the NF Conference, contribute to open-source tools and resources for the NF research community, and promote NF data sharing and reuse. Additional duties as required.

Minimum Qualifications

• MS in Data Science, Ph.D. preferred – Computational Biology, Bioinformatics, or a related field.

• 1-3 years experience in working with public and/or private datasets and large-scale data repositories.

• Strong expertise in data management, analysis, and visualization techniques.

• Experience implementing Claude Science or comparable AI research platforms, including using AI agents for literature review, data analysis, and reproducible computational workflows.

• Demonstrated understanding of, and adherence to, HIPAA regulations and data privacy standards.

• Proven track record of scientific publications and presentations.

• Familiarity with open-source tool development and collaborative research environments.

• Ability to work both independently and within a multidisciplinary team.

• Excellent communication skills.

• Strong organizational skills are needed, which reflect the ability to manage and prioritize multiple tasks seamlessly with precise attention to detail.

• Creative and analytical thinker.

Preferred Qualifications

• Experience integrating multi-omic and clinical datasets for therapeutic target identification and prioritization.

• Experience applying machine learning, AI, or large language model (LLM) tools to biomedical research questions.

• Experience analyzing clinical, real-world, or patient registry data, including patient-reported outcomes.

• Familiarity with neurofibromatosis or rare disease research.

Preferred Skills:

• Programming: R and/or Python, Linux command line, cloud computing

• Omics Analysis: bulk and single-cell RNA-seq, WGS/WES, proteomics, and methylation

• Therapeutic Target Discovery Resources: pathway and network analysis, multi-omic integration, and experience with public resources like GEO, TCGA, GTEx, DepMap, ChEMBL, and Open Targets

• Machine Learning and AI: Claude Science or other LLM-based platforms, experience with agentic AI like Claude Code

• Data Visualization and Reporting: ggplot2, matplotlib, Shiny

• Reproducible Research: Git/GitHub, Docker, Nextflow or Snakemake

• Data Platforms and Standards Domain Knowledge: Synapse, which the NF Data Portal is built on, plus FAIR principles, metadata standards, and ontologies.

Working Conditions, Equipment Used, and Special Information

Must have unimpeachable integrity and trustworthiness and possess remarkable tact, discretion, and professionalism. Verbal and written communication skills will be used daily. Maintains effectiveness under pressure. Ability to lift 25 lbs. Flexible for overnight business travel. Flexible to work evenings and weekends as needed.

Equal Employment Opportunity

CTF and ADP provide equal employment opportunities to all employees and applicants in all Foundation facilities without regard to race, color, religious creed, sex, national origin, ancestry, citizenship status, pregnancy, childbirth, (or related medical conditions, including, but not limited to lactation), physical disability, mental and/or intellectual disability, age, military status or status as a Vietnam-era or special disabled veteran, marital status, registered domestic partner or civil union status, gender (including sex stereotyping and gender identity or expression), medical condition (including, but not limited to, cancer related or HIV/AIDS related), genetic information, or sexual orientation in accordance with applicable federal, state and local laws. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

DISCLAIMER

The above statements are intended to describe the general nature and level of work being performed by the person assigned to this position. They are not intended to be considered an exhaustive list of all responsibilities, duties and skills required.