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Cancer Data Analyst Jobs in Dallas, TX (NOW HIRING)

Novocure

Data Architect

Lavon, TX

$59.25 - $76.25/hr

... cancers. Every role here contributes to that mission - and as a Data Architect, you'll help shape ... Evaluate emerging technologies and architectural approaches that support AI, advanced analytics ...

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Cancer Data Analyst information

See Dallas, TX salary details

$33.6K

$81.8K

$134.5K

How much do cancer data analyst jobs pay per year?

As of Aug 24, 2026, the average yearly pay for cancer data analyst in Dallas, TX is $81,750.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,800.00 and $96,000.00 per year, depending on experience, location, and employer.

What is a cancer data analyst?

A Cancer Data Analyst collects, processes, and analyzes cancer-related data to identify trends, improve patient outcomes, and support research. They work with oncology registries, clinical trials, and healthcare databases to ensure accurate reporting. Their insights help healthcare providers, researchers, and policymakers make data-driven decisions in cancer prevention, treatment, and policy development. Strong statistical and analytical skills, along with knowledge of medical coding and data management, are essential for this role.

What does a cancer data analyst do?

A typical day for a Cancer Data Analyst involves collecting, cleaning, and validating cancer-related data from various sources such as hospital databases or cancer registries. You might spend time analyzing data trends, generating reports, and preparing data visualizations for oncologists, researchers, or public health leaders. Collaboration is frequent, as analysts often participate in multidisciplinary meetings to discuss ongoing studies or quality improvement projects. The work is detailed and requires strong organizational skills but offers the rewarding experience of contributing directly to advancements in cancer research and patient outcomes.

What are the key skills and qualifications needed to thrive as a cancer data analyst?

To thrive as a Cancer Data Analyst, you need a solid background in statistics, epidemiology, or public health, typically supported by a relevant degree or healthcare data experience. Familiarity with data analysis tools like SAS, R, or SQL, and experience with cancer registries or medical coding systems such as ICD-O are often required. Excellent attention to detail, problem-solving skills, and the ability to communicate findings clearly distinguish top performers. These skills ensure precise data analysis, impactful insights, and effective collaboration with researchers and healthcare teams to advance cancer care outcomes.

What are popular job titles related to Cancer Data Analyst jobs in Dallas, TX?

For Cancer Data Analyst jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Cancer Data Analyst jobs in Dallas, TX look for?

The top searched job categories for Cancer Data Analyst jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Cancer Data Analyst jobs?

Cities near Dallas, TX with the most Cancer Data Analyst job openings:

Cancer Data Analyst jobs near you
Infographic showing various Cancer Data Analyst job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $82,098 per year, or $39.5 per hour.

Data Scientist - Innovation - PhD

Irving, TX • On-site

Caris Life Sciences
See more jobs at Caris Life Sciencesexternal

Full-time

Re-posted 11 days ago

Job description

At Caris, we understand that cancer is an ugly word-a word no one wants to hear, but one that connects us all. That's why we're not just transforming cancer care-we're changing lives.
We introduced precision medicine to the world and built an industry around the idea that every patient deserves answers as unique as their DNA. Backed by cutting-edge molecular science and AI, we ask ourselves every day: "What would I do if this patient were my mom?" That question drives everything we do.
But our mission doesn't stop with cancer. We're pushing the frontiers of medicine and leading a revolution in healthcare-driven by innovation, compassion, and purpose.
Join us in our mission to improve the human condition across multiple diseases. If you're passionate about meaningful work and want to be part of something bigger than yourself, Caris is where your impact begins.
Position Summary
Want to help build AI models for the next generation of cancer diagnostics? The models you build here have direct line-of-sight to translational research and clinical decision-making -- work with the potential to shape how cancer is detected, profiled, and treated. As a Data Scientist on the Innovation Team, you will develop machine learning and deep learning algorithms on molecular sequencing data (WGS, WES, RNA-seq, cfDNA), design analytic pipelines for novel biomarker discovery, and tackle the most challenging problems in liquid biopsy and translational oncology research.
About the Team
The Innovation Team is a small, fast-moving R&D group within Caris Life Sciences, drawing on proprietary clinical research data that no other team in oncology can match. We work closely with bioinformaticians, molecular biologists, and clinical scientists to develop high-impact AI models with the potential to shift the landscape of clinical outcomes. You will have the freedom to lead research projects end-to-end -- from problem framing to deployment -- and to shape the methods that drive Caris' R&D agenda. In your first year, success looks like leading one or two research projects from problem framing through deployment, contributing to a peer-reviewed publication or conference submission, and helping shape methods that inform Caris' diagnostic platform.
Job Responsibilities
  • Processing, manipulating, and analyzing large diverse datasets generated from NGS to develop biomarkers for cancer diagnosis, prognosis, and treatment.
  • Developing novel algorithms for feature extraction and biomarker discovery from molecular sequencing data.
  • Applying first-principles analysis to translate open research questions into tractable, well-defined problems.
  • Applying state-of-the-art machine learning and deep learning methods to biological and clinical research questions.
  • Creating rigorous evaluation frameworks and tracking experiments systematically using tools such as MLflow or Weights & Biases.
  • Authoring peer-reviewed research publications and presenting findings at scientific conferences.

Required Qualifications
  • PhD in Data Science, Bioinformatics, Computational Biology, Genomics, Statistics, Computer Science, Engineering, Biophysics, or a related quantitative or biological field.
  • PhD recently completed, or up to approximately 2 years of post-doctoral research experience (academic or industry).
  • Demonstrated work on a cancer biology or translational research problem (PhD thesis chapter, peer-reviewed publication, or postdoc / industry role).
  • Hands-on experience with molecular sequencing data (e.g., WGS, WES, RNA-seq, cfDNA) including production-grade pipelines and analysis.
  • Hands-on experience with generative AI -- large language models, foundation models (e.g., genomic or protein language models), or agentic workflows applied to scientific or clinical data.
  • Proficiency with PyTorch and modern deep learning architectures (transformers, attention mechanisms), with demonstrated application of ML/DL to biological or clinical data.
  • First-author or co-first-author peer-reviewed publications in machine learning venues (e.g., NeurIPS, ICML, ICLR) or in bioinformatics / computational biology journals.
  • Strong Python; comfortable in Linux; proficient with git and collaborative workflows.

Preferred Qualifications
  • Multi-omics integration experience (genomics, transcriptomics, proteomics, methylation, etc.).
  • Experience with epigenetics -- DNA methylation analysis, chromatin biology, or related.
  • Interest in cell-free DNA, liquid biopsy, and next-generation early cancer diagnostics.
  • Interest in novel algorithm development for biomedical signal extraction in sequencing data.
  • Proficiency in cloud platforms (AWS EC2, S3, HealthOmics) and containerization (Docker).

Physical Demands
  • This role primarily involves sedentary work at a computer workstation, including extended periods of typing, reading screens, and virtual or in-person collaboration. Caris provides reasonable accommodations to qualified individuals with disabilities; candidates who need accommodation during the application or interview process are encouraged to contact Caris HR.

Training
All job-specific, safety, and compliance training are assigned based on the job functions associated with this employee.
Other
  • This position is on-site in Irving, TX. The team operates on a fast-iteration research cycle that benefits from close, in-person collaboration.
  • Relocation assistance may be available for qualified candidates.

Conditions of Employment: Individual must successfully complete pre-employment process, which includes criminal background check, drug screening, credit check ( applicable for certain positions) and reference verification.
This job description reflects management's assignment of essential functions. Nothing in this job description restricts management's right to assign or reassign duties and responsibilities to this job at any time.
Caris Life Sciences is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.

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