Data Scientist 1

The Data Scientist 1 supports Cancer Center investigators by applying advanced analytical methods to biological and clinical research datasets. Primary responsibilities include analyzing bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics data; developing and maintaining reproducible workflows; performing quality control, and visualization; and communicating results through written reports and PowerPoint presentations. The individual will work closely with principal investigators (PIs) and research teams to help answer biological questions by applying computing and data science tools to large data sets, and iterate efficiently to deliver reproducible, publication-quality results.

Essential Duties and Responsibilities

* Analyze bulk RNA-seq datasets for Cancer Center PI projects, including quality control, normalization, differential expression, pathway/enrichment analyses, and biological interpretation.

* Analyze single-cell RNA-seq datasets, including QC, normalization, integration/batch correction when appropriate, clustering, cell type/state annotation, differential expression/abundance analyses, and figure generation.

* Analyze spatial transcriptomics datasets, including QC, spatial feature detection, region-based analyses, spatially varying gene identification, cell type mapping/deconvolution (as applicable), and spatial interaction/neighborhood analyses.

* Work collaboratively with Cancer Center PIs and research teams to refine scientific questions, define analysis plans, and iterate on methods and results until the biological objectives are addressed.

* Communicate analytical results clearly to technical and non-technical audiences through oral presentations, collaborative working sessions, and well-structured written reports. Contribute written sections suitable for manuscripts, grants, and presentations.

* Develop, maintain, and document reproducible analysis workflows using R and Python; apply version control and best practices for reproducibility and transparency.

* Use established bioinformatics software and toolchains to support RNA-seq, single-cell, and spatial analyses; select and justify methods appropriate to each study design and dataset.

* Operate effectively in high-performance computing (HPC) environments, including Linux command-line workflows, secure data transfer, job scheduling, and resource-aware computation for large datasets.

* Maintain data integrity and provenance by validating inputs/metadata, documenting assumptions and parameters, and ensuring repeatable analytic outputs.

* Contribute to team knowledge-sharing through SOPs, documentation, and internal training on analysis methods and computational workflows, as needed.

Minimum Qualifications

* Bachelor's degree in Biology, Computer Science, Bioinformatics, Biostatistics, Data Science, or a closely related field.

* Relevant experience performing data analysis and/or bioinformatics workflows.

* Working proficiency in R and Python for data analysis, visualization, and workflow development.

* Ability to work in Linux and HPC environments (command line, remote systems, batch jobs) and to manage large datasets efficiently.

* Strong written and verbal communication skills, including the ability to explain analytical results and limitations to biomedical researchers and to produce clear, actionable reports.

* Demonstrated ability to work collaboratively with investigators and project teams, manage priorities across multiple projects, and meet deadlines.

Knowledge, Skills, and Abilities

* Strong analytical reasoning, statistical thinking, and structured problem-solving for complex, ambiguous research questions.

* Ability to design and implement integrated analytical solutions; sound judgment in method selection and interpretation.

* Ability to create clear, publication-quality visualizations and to communicate results and caveats effectively.

* Familiarity with common bioinformatics data formats and software ecosystems used for RNA-seq, single-cell, and spatial analyses.

* Proficiency in programming and scripting; ability to write maintainable, well-documented code and to troubleshoot effectively.

* Ability to work effectively with diverse stakeholders and maintain productive, consultative relationships with PIs and research staff.

* Organizational skills to manage multiple concurrent projects and maintain reproducible records of analyses, parameters, and deliverables.

The University of New Mexico Comprehensive Cancer Center is the Official Cancer Center of New Mexico and the only National Cancer Institute-designated Cancer Center in a 500-mile radius. Its 136 board-certified oncology specialty physicians include cancer surgeons in every specialty (abdominal, thoracic, bone and soft tissue, neurosurgery, genitourinary, gynecology, and head and neck cancers), adult and pediatric hematologists/medical oncologists, gynecologic oncologists, and radiation oncologists. They, along with more than 600 other cancer healthcare professionals (nurses, pharmacists, nutritionists, navigators, psychologists and social workers), provide treatment to 65% of New Mexico's cancer patients from all across the state. And they partner with community health systems statewide to provide cancer care closer to home. In 2024 they treated more than 15,000 patients in almost 105,000 ambulatory clinic visits in addition to in-patient hospitalizations at UNM Hospital. A total of 2,075 patients participated in cancer clinical trials to study new cancer treatments that include tests of novel cancer prevention strategies and cancer genome sequencing. The more than 123 cancer research scientists affiliated with the UNM Cancer Center were awarded $38.3 million in federal and private grants and contracts for cancer research projects. Since 2015, the physicians, scientists and staff have provided education and training experiences to more than 750 high school, undergraduate, graduate, and postdoctoral fellowship students in cancer research and cancer health care delivery.

Website: unmhealth.org/cancer

See the Position Description for additional information.

• Employees who provide services or work in patient care or clinical areas are required to be in compliance with the University's influenza vaccination requirement.

Bachelor's degree in a relevant field; at least 3 years of experience directly related to the duties and responsibilities specified.

Completed degree(s) from an accredited institution that are above the minimum education requirement may be substituted for experience on a year for year basis.

* Master's degree in a relevant field (preferred).

* Demonstrated experience in bioinformatics, particularly transcriptomics and/or cancer biology.

* Hands-on experience delivering end-to-end analyses for one or more of: bulk RNA-seq, single-cell RNA-seq, spatial transcriptomics.

* Experience with reproducible research practices (e.g., Git-based workflows, containers, workflow tools), and preparing analysis outputs for publication.

* Experience supporting multiple investigators and translating scientific questions into practical analysis plans with iterative stakeholder feedback.

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Positions posted with a Staff Type of Regular or Term are eligible for the Veteran Preference Program. See the Veteran Preference Program webpage for additional details.

The University of New Mexico is committed to hiring and retaining a diverse workforce. We are an Equal Opportunity Employer, making decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability, or any other protected class.

The University of New Mexico requires all regular staff positions successfully pass a pre-employment background check. This may include, but is not limited to, a criminal history background check, New Mexico Department of Health fingerprint screening, New Mexico Children, Youth, and Families Department fingerprint screening, verification of education credentials, and/or verification of prior employment. For more information about background checks, visit https://policy.unm.edu/university-policies/3000/3280.html. Refer to https://policy.unm.edu/university-policies/3000/3200.html for a definition of Regular Staff.