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Data Science Phd Jobs in Arizona (NOW HIRING)

Master's or PhD in Computer Science, Data Science, Statistics, or a related field. * 10-15 years of experience in AI/data science, with at least 5 years in a leadership role. * Proven experience ...

Master's or PhD in Computer Science, Data Science, Statistics, or a related field. * 10-15 years of experience in AI/data science, with at least 5 years in a leadership role. * Proven experience ...

Master's degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or ... Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations ...

Master's degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or ... Advanced degree (Master's or PhD) in a relevant field (Statistics, Machine Learning, AI, Operations ...

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Data Science Phd information

What is a data science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.

What are the key skills and qualifications needed to thrive as a data science PhD?

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What are some common challenges faced by data science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What can I do with a data science PhD?

A data science PhD prepares individuals for advanced roles in research, analytics, and machine learning across industries such as technology, finance, healthcare, and academia. Graduates can work as data scientists, machine learning engineers, research scientists, or data analysts, often utilizing programming languages like Python or R and tools such as TensorFlow or SQL. The degree also enables roles involving complex data modeling, statistical analysis, and developing innovative data-driven solutions.

What are popular job titles related to Data Science Phd jobs in Arizona?

For Data Science Phd jobs in Arizona, the most frequently searched job titles are:

What cities in Arizona are hiring for Data Science Phd jobs?

Cities in Arizona with the most Data Science Phd job openings:

Infographic showing various Data Science Phd job openings in Arizona as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution.

Data Scientist, Data & Science Solutions

Tempe, AZ • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


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
Caris Life Sciences is seeking a data scientist to expand, test, and validate a suite of molecular biomarkers aimed to improve the standard of care for patients undergoing treatment for cancer. This is a research role within the Caris signature development program and responsibilities will center on statistical or machine-learning derived predictions of phenotypic treatment response built from the genotypic data types available on Caris molecular sequencing platforms. A successful candidate will have the analytical, code-oriented mindset to create reproducible data science pipelines, and the communication skills to discuss the implications of the scientific results with our medical professionals.
Job Responsibilities
  • Contribute to analytics and research that support internal stakeholders and external partners.
  • Assist in the development and evaluation of molecular signatures and analytical approaches that leverage Caris' data to support partner research and drug discovery strategies.
  • Support preparation of analytical results and figures for internal reviews and client-facing discussions.
  • Develop and maintain tools, workflows, and automated solutions to scale data analytics and data science operations.
  • Support the Biopharma Solutions team with feasibility assessments and tooling to optimize workflows.
  • Write well-structured, well-documented, and reproducible code, including efficient queries and organized codebases.

Required Qualifications
  • PhD in Computational Biology, Bioinformatics, Mathematics, Data Science, Engineering, or related scientific field.
  • Strong programming skills in Python or R, with experience developing reproducible analysis workflows.
  • Experience with Linux ecosystem, Git, and queries from SQL or related database families.
  • Experience with molecular genetics data and/or multimodal real-world data (RWD).
  • Ability to translate biological and scientific questions into analytical or statistical approaches and deliver data-driven insights.
  • Strong verbal and written communication skills, with the ability to explain complex technical concepts in clear language.

Preferred Qualifications
  • Experience with interpretation of clinical health records including Electronic Health Records, insurance claims data, or patient histories.
  • Experience collaborating directly with external partners or clients, particularly in biopharma or healthcare.
  • Good code documentation practices and experience with workflow management packages.
  • Experience working in cloud or HPC clusters.

Physical Demands
  • Will work at a computer most of the time, with some time spent collaborating with subject matter experts and business group leaders either in person or through remote conferencing.
  • Visual acuity and analytical skill to distinguish fine detail.
  • Must possess ability to sit and/or stand for long periods of time.

Training
  • All job specific, safety, and compliance training are assigned based on the job functions associated with this employee.

Other
  • This position may require periodic travel and some evenings, weekends, and/or holidays.

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.