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Data Scientist Data Jobs in Arizona (NOW HIRING)

The ideal candidate combines expertise in data science, automation, AI/ML, computer vision, and software development with a passion for solving complex manufacturing problems. You will play a key ...

$49K/yr

Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is ...

Data Scientist

Phoenix, AZ · On-site

$136K - $164K/yr

Data Scientist III (Generative AI) Location: Phoenix, AZ Start Date: ASAP Duration: Permanent Compensation: $136,900 - $164,300 Benefits: Eligible for Health, Dental, Vision, 401K, PTO Must be ...

ET-D&AI provides data science support to internal business partners across State Farm, including work focused on enhancing customer engagement and digital experiences through AI/ML. Responsibilities ...

Why Join Our Data Science Team? At State Farm, we are dedicated to helping our team members develop to their full potential. As a Data Scientist, you have the unique opportunity to develop both ...

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong experience in Generative AI, traditional Machine Learning, and ML Ops. The ideal candidate will have ...

Data Scientist / Senior Data Scientist We are seeking a highly skilled Data Scientist with strong experience in Generative AI, traditional Machine Learning, and ML Ops. The ideal candidate will have ...

Requirements: • Bachelor's degree required in Mathematics, Data Science, Computer Science, Engineering, Physics, or another quantitative discipline; advanced degree preferred. • Strong technical ...

The Data Scientist will play a crucial role in developing advanced analytics and machine learning solutions to enhance supply chain efficiency and operational performance. Responsibilities : • ...

We are seeking a highly analytical and hands-on Data Scientist to join a team building data-driven personalization solutions while helping drive the organization''s transition into Generative AI and ...

Data Scientist

Scottsdale, AZ · On-site

$80K - $120K/yr

Savas Software/Lifekind Health is seeking a technically strong, impact-driven Data Scientist with experience building ML-based predictive products and advanced analytics (including LLM based) in real ...

The Data Scientist will serve as a key contributor to the company's data and analytics strategy, partnering with manufacturing, supply chain, quality, and IT stakeholders to deliver advanced ...

The Data Scientist will serve as a key contributor to the company's data and analytics strategy, partnering with manufacturing, supply chain, quality, and IT stakeholders to deliver advanced ...

Data Scientist

Phoenix, AZ · On-site

$190K - $269K/yr

Advanced Packaging Technology and Manufacturing (APTM) Yield Organization is looking for a Data Scientist who will work for manufacturing data analysis, assembly yield modeling and AL/ML, agentic AI ...

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Data Scientist Data information

What is the difference between Data Scientist Data vs Data Analyst?

AspectData Scientist DataData Analyst
Required CredentialsDegree in Data Science, Statistics, or related fields; often includes certifications in machine learning or data analysis toolsDegree in Statistics, Mathematics, or related fields; certifications in data visualization or analysis tools are common
Work EnvironmentDevelops predictive models, advanced analytics, and machine learning algorithms; often in R&D or data science teamsPrepares reports, visualizations, and interprets data for business decisions; typically in business intelligence teams
Employer & Industry UsageUsed across tech, finance, healthcare, and e-commerce industries for complex data modelingCommon in retail, marketing, finance, and healthcare for reporting and data interpretation

While both roles analyze data, Data Scientist Data focuses on building predictive models and advanced analytics, whereas Data Analysts primarily interpret data and generate reports for decision-making. The roles often overlap but differ in complexity and scope.

What are some common challenges Data Scientists face when working with large datasets, and how can they be addressed?

Data Scientists often encounter challenges such as data quality issues, scalability concerns, and long processing times when working with large datasets. To address these, it's common to use distributed computing tools like Apache Spark or Hadoop, and to implement efficient data cleaning and preprocessing pipelines. Collaborating closely with data engineers can also help optimize data storage and retrieval. Additionally, adopting best practices in code versioning and documentation ensures that models and analyses are reproducible and scalable as data grows.

What are Data Scientists?

Data Scientists are professionals who analyze and interpret complex digital data to help organizations make informed decisions. They use a combination of statistics, machine learning, programming, and domain expertise to extract insights from large datasets. Data Scientists often work with tools such as Python, R, and SQL, and collaborate with teams to develop predictive models, visualize data, and solve business problems. Their work is crucial in fields like finance, healthcare, technology, and marketing.

What are the key skills and qualifications needed to thrive as a Data Scientist, and why are they important?

To thrive as a Data Scientist, you need strong analytical skills, proficiency in statistics, and experience with data modeling, often supported by a degree in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks, and data visualization tools such as Tableau or Power BI is typically required. Strong problem-solving abilities, effective communication, and curiosity help a Data Scientist translate complex data into actionable insights. These skills are vital for extracting value from data, informing business decisions, and driving innovation within an organization.

Data Scientist / Data Scientist, Senior

APS

Phoenix, AZ

Other

Re-posted 15 days ago


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Job description

Our present and future success depends on the creative and dedicated people of our company who demonstrate the principles outlined in the APS Promise: Design for Tomorrow, Empower Each Other and Succeed Together.  

Summary

Data Scientist / Data Scientist, Senior

Are you a Data Scientist / Data Scientist, Senior ready to make a big impact at scale? We're looking for a highly skilled Data Scientist / Data Scientist, Senior to lead the design and deployment of production-grade machinelearning systems in a complex enterprise environment. You'll own the full MLOps lifecycle-from prototyping tomonitoring-and architect solutions that power intelligent, real-time decision-making across critical businessfunctions.
This is a high-visibility role where you'll collaborate with cross-functional teams, influence architecture, and helpdefine best practices that shape the future of ML at scale.

What You'll Do:

  • Lead MLOps Initiatives: Design, build, deploy, and monitor end-to-end ML solutions that are scalable,reliable, and secure.
  • Architect for Scale & Speed: Build applications optimized for low latency on high-volume data pipelinesand streaming environments.
  • Advise & Innovate: Act as a thought partner to data scientists and engineering leaders, bringing deepdomain expertise in ML model design and infrastructure.
  • Collaborate Cross-Functionally: Work with enterprise architects, product teams, and data scientists todeliver real-world business value.
  • Own Quality & Governance: Establish and maintain best practices for ML lifecycle management, includingCI/CD, monitoring, testing, and documentation.

You'll Be a Great Fit If You Have:

  • Held a Machine Learning Engineer or MLOps role in a large-scale enterprise environment.
  • Deep experience with modern ML models, cloud-native data platforms, and orchestration tools (e.g.,Kubeflow, SageMaker, MLflow).
  • Proven ability todesign scalable ML architecturesfor streaming and batch use cases.
  • A mindset formentorship and technical leadership, with the ability to guide teams on best practices inproduction ML.

Sponsorship for U.S. work authorization is not available for this position, now or in the future.

Minimum Requirements

Data Scientist 

  • BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related field
  • PLUS minimum four(4) years directly related data analytics, data science, predictive modeling, machine learning, statistical modeling and/or user experience role
  • OR advanced degree and two (2) years directly related experience.
  • Possesses a combination of strong analytical and problem-solving skills and programming knowledge, or an equivalent combination of education and experience with demonstrated comparable knowledge and abilities.

Data Scientist, Senior

  • BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related field
  • PLUS minimum six (6) years directly related data analytics, data science, predictive modeling, machine learning, statistical modeling and/or user experience role
  • OR advanced degree and four (4) years directly related experience.
  • Possesses a combination of strong analytical and problem-solving skills and programming knowledge, or an equivalent combination of education and experience with demonstrated comparable knowledge and abilities.
    Preferred Special Skills, Knowledge or Qualifications:
  • Masters or Doctorate degrees in related fields. 
  • Knowledge/experience in utility industry and business functions.
  • Certification in Data Science and/or predictive analytics
  • A high level of proficiency in commonly used programming languages and tools like R Programming, Python and SQL.
  • Strong communication, presentation and writing skills.
  • Must be able to lead teams in evaluations and implementation of solutions.
  • Must be able to work with key internal and external stakeholders and all levels of management.
Major Accountabilities

1) Collaboration with customers and partners:
- Consult with stakeholders and subject matter experts to understand business needs and operations, goals and objectives and key drivers for performance.
- Work closely with the business units to complete data analytics efforts. Build and maintain strong working relationships with customers, partners and vendors. 
2) Data requirements and preparation: 
- Identify available and relevant data and the data sources.
- Collaborate with SMEs, data stewards and architects for data collection, preparation, integration, quality, exploration and retention.
- Gather data, formulate cluster or nodes and establish performance checks on the large data models.
- Design and implementation of solutions including data acquisition, storage, transformation, and analysis
3) Modeling and Deployment: 
- Design, develop and deploy innovative models. Provide insights from predictive statistical modeling activities. Test theories by creating models and experimenting with data.
- Design models, algorithms and visualizations that help distill insights from huge volumes of chaotic data.
- Modeling complex problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques using existing or new front-end reporting & analytics tools.
- Play key role in turning data into critical information and knowledge that can be used to make sound organizational decisions.
- Propose innovative ways to look at problems by using data mining approaches and validate findings using experimental and iterative approaches.
- Understand data transforming platforms and technologies and maintain a knowledge of discipline maturity.
4) Present results, provide recommendations and lead analytics efforts:
- Present findings to the business in a way that can be easily understood by business counterparts. 
- Make recommendations based on business requirements and knowledge of industry best practices.
- Make technical decisions on advanced analytics initiatives.
5) Programming and Coding
- Utilize programming language, such as R, Python, SQL, .net, Java or C++ to evoke the data from data source and model
- Familiarity with Cloud structure and building, utilizing cloud technologies
- Performing data acquisition using JSon, SQL, ODBC, JScript, or API for Big Data extracts
- Transform and utilize streaming data with programming languages such as: KAFKA, SQL, Spark, and/or Azure
6) Mentoring and coaching junior staff as necessary

Export Compliance / EEO Statement

This position may require access to and/or use of information subject to control under the Department of Energy's Part 810 Regulations (10 CFR Part 810), the Export Administration Regulations (EAR) (15 CFR Parts 730 through 774), or the International Traffic in Arms Regulations (ITAR) (22 CFR Chapter I, Subchapter M Part 120) (collectively, 'U.S. Export Control Laws'). Therefore, some positions may require applicants to be a U.S. person, which is defined as a U.S. Citizen, a U.S. Lawful Permanent Resident (i.e. 'Green Card Holder'), a Political Asylee, or a Refugee under the U.S. Export Control Laws. All applicants will be required to confirm their U.S. person or non-US person status. All information collected in this regard will only be used to ensure compliance with U.S. Export Control Laws, and will be used in full compliance with all applicable laws prohibiting discrimination on the basis of national origin and other factors. For positions at Palo Verde Nuclear Generating Stations (PVNGS) all openings will require applicants to be a U.S. person.
Pinnacle West Capital Corporation and its subsidiaries and affiliates ('Pinnacle West') maintain a continuing policy of nondiscrimination in employment. It is our policy to provide equal opportunity in all phases of the employment process and in compliance with applicable federal, state, and local laws and regulations. This policy of nondiscrimination shall include, but not be limited to, recruiting, hiring, promoting, compensating, reassigning, demoting, transferring, laying off, recalling, terminating employment, and training for all positions without regard to race, color, religion, disability, age, national origin, gender, gender identity, sexual orientation, marital status, protected veteran status, or any other classification or characteristic protected by law.
For more information on applicable equal employment regulations, please refer to EEO is the Law poster. Federal law requires all employers to verify the identity and employment eligibility of every person hired to work in the United States, refer to E-Verify poster. View the employee rights and responsibilities under the Family and Medical Leave Act (FMLA). Arizona Public Service is a smoke free workplace.

Home based: Home based employees primarily work from their home offices and come into an APS facility on an as-needed basis. 

  • Employees are expected to reside in Arizona (or New Mexico for Four Corners-based employees).  
  • Working from a home office requires adequate technology and an appropriate ergonomic set up.  
  • Role types are subject to change based on business need. 

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