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About the Role
This role involves leading the design and deployment of production-grade machine learning systems within a complex enterprise environment. You will own the full MLOps lifecycle, from prototyping to monitoring, and architect solutions that drive real-time decision-making across critical business functions.
Responsibilities
- Design, build, deploy, and monitor end-to-end scalable and secure ML solutions.
- Build applications optimized for low latency on high-volume data pipelines and streaming environments.
- Act as a thought partner to data scientists and engineering leaders regarding ML model design and infrastructure.
- Collaborate with enterprise architects, product teams, and data scientists to deliver business value.
- Establish and maintain best practices for ML lifecycle management, including CI/CD, monitoring, testing, and documentation.
- Consult with stakeholders to understand business needs, goals, and performance drivers.
- Identify relevant data sources and collaborate on data collection, preparation, and quality assurance.
- Design and deploy innovative predictive models and algorithms.
- Present findings and recommendations to business counterparts in an understandable format.
- Mentor and coach junior staff.
Requirements
- Experience in a Machine Learning Engineer or MLOps role within a large-scale enterprise environment.
- Deep experience with modern ML models, cloud-native data platforms, and orchestration tools.
- Proven ability to design scalable ML architectures for streaming and batch use cases.
- Mindset for mentorship and technical leadership.
- BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering, or related field.
- Minimum four years of related experience for Data Scientist level, or six years for Senior level.
- Advanced degree holders require two years of experience for Data Scientist level, or four years for Senior level.
- Must be a U.S. person as defined by U.S. Export Control Laws.
- Must reside in Arizona or New Mexico for specific locations.
- Ability to maintain a home office with adequate technology and ergonomic setup.
Skills
- Kubeflow
- SageMaker
- MLflow
- R Programming
- Python
- SQL
- .net
- Java
- C++
- Cloud technologies
- JSON
- ODBC
- JScript
- API
- KAFKA
- Spark
- Azure
- Predictive modeling
- Statistical modeling
- Data mining
- Data visualization
Location
- Arizona
- New Mexico
- Home based
Work Type
- Full-time
Experience Level
- 4+ years for Data Scientist
- 6+ years for Senior Data Scientist
Education Level
- BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related field
- Masters or Doctorate degrees preferred
About the Company
- Arizona Public Service (APS)
- Pinnacle West Capital Corporation
Equal Opportunity
- Pinnacle West maintains a policy of nondiscrimination in all phases of the employment process.
- Equal opportunity is provided without regard to race, color, religion, disability, age, national origin, gender, gender identity, sexual orientation, marital status, protected veteran status, or any other classification protected by law.