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Machine Learning Engineer

2 months ago

Phoenix, Arizona, United States APS Full time
Summary

Machine Learning Engineer | Data Scientist | Palo Verde Business Intelligence & Analytics

Join our team as a Data Scientist in the Palo Verde Business Intelligence & Analytics group, where you'll leverage your expertise to uncover new insights and drive business decisions through advanced data analytics.

What your day would be like:

  • Advanced Data Analytics: Work with vast amounts of structured and unstructured data to perform predictive modeling, trend analysis, and "what-if" scenarios that reveal actionable insights for various business units.
  • Innovative Problem-Solving: Apply creative thinking and cutting-edge techniques in machine learning, AI, regression analysis, and both supervised and unsupervised modeling to validate and enhance business operations.
  • Collaborative Intelligence: Partner with subject matter experts, project managers, architects, data engineers, and external vendors to translate data into critical information that supports strategic business decisions.
  • Thought Leadership: Recommend forward-thinking approaches and algorithms that challenge conventional methods, providing thought-provoking ideas that push the boundaries of business intelligence and analytics.
  • Independent & Team-Oriented Work: Operate effectively both independently and within a collaborative team environment, with a strong focus on customer satisfaction and cross-functional collaboration.

The kinds of people we want to talk to have done many of the following:

  • Creative and Analytical Mindset: A curious and innovative thinker with strong analytical abilities and a passion for discovering new opportunities through data.
  • Advanced Technical Skills: Proficiency in machine learning, AI, and other advanced statistical modeling techniques, with a demonstrated ability to build and validate complex mathematical models.
  • Organizational & Communication Skills: Excellent organizational capabilities combined with strong communication skills to articulate complex data insights to diverse stakeholders.

If you are passionate about using data to drive impactful business decisions and thrive in a dynamic, collaborative environment, we invite you to join our team and contribute to the future of business intelligence at Palo Verde.

Minimum Requirements

Machine Learning Engineer | Data Scientist | Palo Verde Business Intelligence & Analytics

  • BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related fields
  • AND minimum four (4) years related business experience in 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.
  • Strong understanding of data analytics methods and tools like R Programming, Python and SQL. Expertise in extracting and transforming large datasets.
  • Proficient at integrating and preparing large, varied datasets, architecting specialized database and computing environments/platforms, and communicating results.
  • Excellent written and communications skills.

Preferred Special Skills, Knowledge or Qualifications:

  • Masters or Doctorate degrees in related fields.
  • Knowledge/experience in utility industry and business functions.
  • Certification in machine learning and deep learning and/or predictive analytics
  • Knowledge of Linux, Docker and Kubernetes (Dev Ops Engineering)
  • Knowledge/Experience in Natural Language Processing
  • Familiar with TensorFlow

Nuclear requirement: Any PVNGS employee may be called upon to serve as a member of the Emergency Response Organization (ERO) and will be expected to fulfill their obligation as an ERO member. Any PVNGS employee may be called upon to support a refueling or short-notice outage. This includes line roles and responsibilities as necessary to execute outage activities. These are a condition of employment at PVNGS.

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/Process data 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

Read the full posting.