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Phd Computer Science Jobs in Phoenix, AZ (NOW HIRING)

onsemi

Sr. Manager AI & Data Science

Scottsdale, AZ · On-site

Required : • 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. • ...

USAA

Data Scientist Senior

Phoenix, AZ

... PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative discipline and 4 years of experience in predictive ...

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Axon

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92.20K - $125.90K/yr

PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML Scientist experience in Computer Science or a related field with a focus on LLM, MLLMs, Computer ...

DataAnnotation

Decision Scientist

Phoenix, AZ · On-site +1

$40/hr

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g ...

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How much do phd computer science jobs pay per year?

As of May 28, 2026, the average yearly pay for phd computer science in Phoenix, AZ is $82,519.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,000.00 and $92,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a PhD in Computer Science, and why are they important?

To thrive as a PhD in Computer Science, you need advanced expertise in algorithms, programming, and research methodologies, typically supported by a doctoral degree in computer science or a related field. Mastery of programming languages (such as Python, Java, or C++), data analysis tools, and familiarity with version control systems like Git are commonly required, along with experience in publishing academic research. Critical thinking, problem-solving, strong written and verbal communication, and perseverance are vital soft skills for success in research and collaboration. These skills and qualifications are essential for making significant contributions to the field, driving innovation, and effectively sharing knowledge with the academic and professional community.

What are some common challenges faced by PhD Computer Science students during their research?

PhD Computer Science students often encounter challenges such as defining a clear and impactful research problem, managing long-term projects with limited guidance, and coping with the pressure to publish in top-tier conferences or journals. Balancing coursework, teaching responsibilities, and research can also be demanding. Effective time management, networking with peers and mentors, and seeking regular feedback can help students navigate these challenges and achieve their academic goals.

What is a PhD in Computer Science?

A PhD in Computer Science is the highest academic degree in the field, focused on advanced research and the creation of new knowledge in computing. It typically involves several years of coursework followed by original research culminating in a dissertation. Graduates often pursue careers in academia, research, or advanced industry roles that require deep technical expertise and problem-solving skills.

Is IT worth doing a PhD in CS?

A PhD in Computer Science can be valuable for careers in research, academia, or specialized industry roles requiring advanced expertise. It typically involves several years of study, research, and publication, and can lead to higher-level positions but may not be necessary for most industry jobs that value practical skills and experience. Consider your career goals and whether the research focus aligns with your interests before pursuing a PhD.
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Phd Computer Science jobs near you
Infographic showing various Phd Computer Science job openings in Phoenix, AZ as of May 2026, with employment types broken down into 3% As Needed, 57% Full Time, 21% Part Time, 16% Contract, and 3% Nights. Highlights an 57% Physical, 9% Hybrid, and 34% Remote job distribution, with an average salary of $82,519 per year, or $39.7 per hour.
Computational Scientist - AI Trainer

Computational Scientist - AI Trainer

DataAnnotation

Phoenix, AZ • On-site, Remote

$40/hr

Full-time

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

Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr

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