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Data Science Machine Learning Jobs in Arizona (NOW HIRING)

Sr. Analyst, Data Science

Tempe, AZ · On-site

$85.90K - $143.17K/yr

This role is ideal for a data scientist who is equally comfortable writing code, building models ... Machine Learning & Modeling * Build, validate, and deploy supervised and unsupervised machine ...

Experience implementing and supporting endtoend Machine Learning workflows and patterns * Expert level programming skills in Python and experience with Data Science and ML packages and frameworks

Data Engineer - Remote

Chandler, AZ

$116.90K - $140.40K/yr

We want data science/machine learning/data analyst and Java Full stack candidates. Required skills for Java/Full stack/DevOps positions: * Bachelors degree or Masters degree in Computer Science ...

Junior Software Developer

Tucson, AZ

$64.60K - $83.90K/yr

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions ...

Stay up to date with the latest trends and technologies in data science and machine learning. * Ability to work independently and collaborate as part of a team * Effective written and verbal ...

Stay up to date with the latest trends and technologies in data science and machine learning. * Ability to work independently and collaborate as part of a team * Effective written and verbal ...

... machine learning platforms data science expertise in statistical modeling, predictive analytics, and business intelligence using Python, R, SQL, and advanced analytics frameworks, implementing ...

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Data Science Machine Learning information

See Arizona salary details

$34.9K

$114.4K

$183.1K

How much do data science machine learning jobs pay per year?

As of Jun 1, 2026, the average yearly pay for data science machine learning in Arizona is $114,378.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,800.00 and $126,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Machine Learning professional, and why are they important?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What are some common challenges faced when deploying machine learning models as a Data Science Machine Learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

Other

Posted 26 days ago


Job description

Role: Data Scientist
Work Location & Reporting Address: Phoenix, AZ (Onsite)
Contract duration (in months): 6-12
Job Details:
Must Have Skills:

  • Data Science
  • Statistical modelling
  • Python
Detailed Job Description:
  • Looking for a senior data scientist with good statistical and modelling knowledge.
  • Data Scientist specializing in Natural Language Processing NLP, Conversational AI, Generative AI, and Large Language Models LLM, with a strong background in developing machine learning and deep learning models