Cancer Research Data Jobs

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Data Scientist Cancer Neuroscience

MD Anderson Houston, TX

Houston, TX

Today

$107k - $160k/yr Full time Big Data Cancer Research Clinical Data Science

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Job Description

Support cancer neuroscience research by building reliable data infrastructure, analytical workflows, and predictive modeling capabilities for CNP projects.

Responsibilities

Create and maintain a structured, up-to-date inventory of neuro-focused datasets, cohorts, registries, biospecimen-linked datasets, clinical data assets, imaging datasets, patient-reported outcomes, molecular datasets, and other relevant research resources.
Document institutional data asset attributes, including dataset ownership, access requirements, data dictionaries, cohort definitions, refresh cadence, data limitations, analytical readiness, and potential research use cases.
Act as a technical connector between CNP-supported investigators, neuro-focused research initiatives, institutional data teams, the Institute for Data Science in Oncology, the institutional Research Data Office, and other enterprise stakeholders to improve awareness, responsible use, and strategic alignment.
Find opportunities to harmonize, link, reuse, and scale CNP-aligned datasets while reducing duplicative data collection and supporting governance, documentation, and interoperability standards.
Help CNP leadership use inventory and analytical outputs for project prioritization, infrastructure planning, collaboration opportunities, grant development, philanthropy reporting, and long-range strategic planning.
Design, build, maintain, and document data pipelines for prospective and retrospective oncology cohorts, including clinical, research, operational, and multimodal datasets.
Collect, clean, harmonize, preprocess, and validate data from multiple sources to support accuracy, completeness, usability, and reproducibility.
Develop and maintain transparent, auditable, and well-commented code bases for routine and advanced data science tasks.
Create reusable workflows, templates, and documentation that support efficient data access, analysis, reporting, and collaboration across CNP-supported projects.
Work with large datasets using Python, R, SQL, Spark, Foundry, Microsoft Fabric, AWS, Azure, GCP, or comparable environments.
Conduct exploratory data analysis to identify trends, patterns, anomalies, missingness, bias, and potential signals relevant to cancer neuroscience research.
Develop, test, validate, and refine predictive and prescriptive models using statistical methods, machine learning, artificial intelligence, and other advanced techniques.
Design and implement analytical experiments to validate hypotheses, evaluate model performance, and support scientific decision-making.
Provide onboarding, hands-on training, and technical support to research staff and project teams using Foundry and related institutional platforms, including best practices for access, workflow development, documentation, and collaboration.
Assist users with analytical question definition, technical issue resolution, workflow improvements, and translating research needs into feasible data science approaches.
Collaborate with clinicians, laboratory scientists, data scientists, data engineers, statisticians, bioinformaticians, research staff, and program leadership to optimize data insights and support CNP priorities.
Communicate findings via visualizations, dashboards, reports, presentations, and clear written summaries for technical and non-technical audiences.
Collaborate on scientific publications, abstracts, grant applications, technical reports, and other documentation for faculty, leadership, advisory boards, philanthropy, and project teams.
Prepare technical reports and other documentation for upper management and team members for short- and long-range projects and planning.
Contribute to institutional data integration by aligning CNP-specific data needs with broader IDSO-supported platforms, standards, and analytical capabilities.
Ensure data governance, privacy, security, documentation, and compliance standards are followed in all data science activities.
Stay current with emerging data science, machine learning, artificial intelligence, clinical informatics, and big data technologies.
Other duties as assigned.

Requirements

Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.
Three years of scientific software or industry development/analysis experience.
With a Master's degree: one year required experience.
With a PhD: no experience required.

Technologies

Python, R, SQL, Spark
Foundry
Microsoft Fabric
AWS, Azure, GCP

Benefits

Medical
Dental
Paid time off
Retirement
Tuition benefits
Educational opportunities
Individual and team recognition

Preferred

Experience in academic healthcare, oncology, cancer research, clinical research, translational research, or biomedical research.
Experience working with EPIC-derived clinical data, electronic health record data, prospective or retrospective cohorts, clinical registries, institutional research datasets, real-world clinical data, or multimodal biomedical datasets.
Experience with Foundry or similar enterprise data platforms.
Experience developing analytical workflows, dashboards, technical reports, reusable data products, or data pipelines for research or operational stakeholders.
Experience contributing to peer-reviewed publications, abstracts, grant applications, scientific presentations, philanthropy reports, or institutional strategy documents.
Experience with machine learning, natural language processing, large language model-enabled workflows, or AI applications in healthcare or research settings.
Experience working collaboratively with clinicians, scientists, statisticians, bioinformaticians, data engineers, research staff, and institutional data teams.

Education

Preferred: Master's degree or PhD in Science, Engineering, Data Science, Computer Science, Statistics, Biomedical Informatics, Computational Biology, Bioinformatics, Biostatistics, Public Health, or related field.

Additional Information

Requisition ID: 183428
Employment Status: Full-Time
Employee Status: Regular
Work Week: Days
Work Location: Houston, TX (onsite)
Work Location: Hybrid Onsite/Remote
Pivotal Position: Yes
Referral Bonus Available?: Yes
Relocation Assistance Available?: Yes
FLSA: Exempt and not eligible for overtime pay
Fund Type: Soft
Salary: USD 106,500 - 159,500 per year
Minimum Salary: USD 106,500
Midpoint Salary: USD 133,000
Maximum Salary: USD 159,500
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